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Alizadeh Elaheh Alizadeh, Ph.D. |
Farmington, CT |
I use image processing and shape quantification methods to extract information from imaging data and link them to phenotypes by machine learning approaches.
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My project focuses on combining spatial transcriptomics and imaging data to predict phenotypes in cancer and other diseases. In my previous research I developed TISMorph software (in Matlab) to add new cell shape features which common software were not able to capture. Then I used these features to distinguished between cancer and normal cells with single cell resolution and predicted the function of novel kinases. I also mathematically modeled nuclear Beta-catenin's switch like response to WNT stimulation. During my last four years I have worked closely with biologists, developed a pipeline for them in R, and mentored them to analyze, automatically label plate-based assays and visualize their data.
Elaheh Alizadeh on ORCID
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Bioinformatics|Cancer|Computational Biology |
Bioinformatics|Cancer|Computational Biology |
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Computational Scientist |
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Angello Bri Angello, B.S. |
Farmington, CT |
"As you navigate through the rest of your life, be open to collaboration. Other people and other people's ideas are often better than your own. Find a group of people who challenge and inspire you, spend a lot of time with them, and it will change your life." ~ Amy Poehler
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Bri started with JAX, as an IT Project Manager, in April 2016, where she was involved in many key projects, including the launch of CKB’s public site ahead of the ASCO conference in 2016, aiding MCGI during their establishment, and the implementation of the separate clinical infrastructure at JAX Genomic Medicine in Farmington. Bri most recently supported the IT infrastructure team with multiple cloud based collaboration initiatives aimed to improve the means by which our staff collaborate; not only with each other, but external partners and researchers around the globe. These initiatives involved enabling the secure use of Google Genomics Cloud Platform, implementing Webex for video and audio collaboration, migrating TIS to Webex from Adobe connect for their educational Webinars, and bringing JAX a secure, cloud based storage solution that can be accessed from any device anywhere in the world with Box.
Bri has been a project manager since 2011, working in various fields including insurance, pharmaceuticals, and manufacturing, and holds a BS in Physician Assistant Studies, Public Health, and Related Clinical Sciences.
She is looking forward to bringing her skills to the Computational Sciences department.
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Computational Biology |
Computational Biology |
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Bates Jennifer Bates |
Farmington, CT |
Office Administrator for the Director of Computational Sciences, the Director of Statistics, Analysis and Scientific Computing and their labs of 30 Postdoctoral Scientists
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Well-organized and proficient at multitasking and prioritizing. Hardworking, dedicated professional with extensive experience in Office Administration/HR Management. A strong work ethic with a commitment to integrity and excellence. A team player fostering trust and building strong relationships. Ability to work in any organization. I have provided administrative support for High Level Senior Directors. Expert in submitting Concur requests. Prescreens all candidates via phone and face-to-face interviews. Onboarding of new and exit interviews with departing employees. Equipment and software procurement. Video/room conference scheduling across multiple locations. Monthly reporting including transaction research. Expense submission and reimbursement. Partner with Human Resources.
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Berger Alexander Berger, B.S. |
Bar Harbor, ME |
I use software engineering to solve complex problems in scientific software and scientific software systems.
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I have a B.S. in Applied Mathematics from NYC College of Technology. I started my time at Jax in 2014 as a Software Quality Assurance Intern, joined Computational Sciences as an Associate Scientific Software Engineer in 2016 and became a Scientific Software Engineer in 2018. I'm a "full-stack" engineer who works on a variety of problems including genomics algorithm optimization in C/C++, RESTful API design and implementation using Flask, software reliability engineering, cloud computing, and project and systems design. I'm currently pursuing an M.S. in Computer Science as a member of the inaugural class at The Roux Institute at Northeastern.
Visit the Roux Institute
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Alex Berger on GITHUB
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Software Engineer |
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Bluis John Bluis, M.S.,B.S. |
Farmington, CT |
My primary areas of interest are software engineering, bioinformatics, and genomics.
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I received my M.S. in Computer Science and Engineering and B.S. in Ecology and Evolutionary Biology from the University of Connecticut researching biological databases and ontologies. For over ten years I have been leading the development of web applications for multiple Fortune 500 companies in a number of industries including environmental safety, facility maintenance, and media.
I am excited to be bringing my research and industry experience to The Jackson Laboratory community and contributing to the development of robust, innovative software designed to help us solve some of the most complex problems facing the biomedical community today.
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Computational Biology|Bioinformatics|Genetics and Genomics |
Computational Biology|Bioinformatics|Genetics and Genomics |
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Castellanos Francisco Castellanos, M.S. |
Farmington, CT |
My research interest is in Data Science/Data Engineering within the domain of Bioinformatics and Genome research.
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From the early days of my career, while designing and writing programs, from assembler, to C++, to SQL, to JAVA/J2EE, to NoSQL, to front-end JavaScript framework languages; my passion has been Software Development and Architecture, and the interesting study of surging technologies thereof.
My professional background includes experiences in various industries and in diverse capacities which have giving me the opportunity to understand end-to-end intricacies of software development life cycles and software platforms. During my career, I have had the opportunity to plan, architect, develop, and lead software projects and teams with the ultimate goal of providing solutions that meet and exceed stakeholder’s expectations. My 15 years of work experience includes serving in various arenas, such as Supply Chain, E-Commerce Software Platforms, and Insurance industries
I recently joined JAX, and I am absolutely thrilled with the opportunity to contribute to the goal of research for tomorrow’s cures and personalized treatments. The world of genome research
and bioinformatics is absolutely fascinating, so I am enthusiastic to apply my skills and to broaden my knowledge as a dive deeper into this great domain and inspiring cause.
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Bioinformatics|Computational Biology|Cancer|Genetics and Genomics |
Bioinformatics|Computational Biology|Cancer|Genetics and Genomics |
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Software Engineer |
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Chandok Harshpreet Chandok, M.S. |
Farmington, CT |
Next Generation Sequencing Analysis, Computational Cancer Biology, Pharmacology, Precision Medicine, Translational Research
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I hold a Masters in Bioinformatics minor in Health Informatics. My dissertation revolved around literature based discovery utilized to mine existing drug interaction evidences in the clinical trial Phase I and II studies and predicting novel drug interaction signals with mentions of adverse related events. Few interesting projects during my masters includes mining the highthroughput data to understand changes in gene expression, methylation and variant profiles in cancers such as Glioblastoma Multiforme and lung cancer using the computational methods and systems biology approaches. My research interests are to apply computational and machine learning approaches to understand the molecular mechanisms and biological complexities in tumors leading to better prediction of treatments.
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Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
The Tewhey Lab |
Bioinformatics/Data Analyst |
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Chaussabel Damien Chaussabel, Ph.D. |
Farmington, CT |
Development of approaches and resources for the analysis, visualization and functional interpretation of large-scale immunological profiling datasets.
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My research has focused on blood transcriptomics and its application in patient-based research. My primary role at the Jackson Laboratory is to support the development of systems immunology and immunoinformatic research capacity – including through the implementation of training programs and the support of projects and investigators conducting immunology research at Jax.
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Damien Chaussabel on ORCID
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Bioinformatics|Computational Biology|Genetics and Genomics|Immune Disorders |
Bioinformatics|Computational Biology|Genetics and Genomics|Immune Disorders |
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Computational Scientist |
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Chen Mandy Chen, Ph.D. |
Bar Harbor, ME |
I am interested in biostatistical analysis, pattern recognition, automation, high performance computing, full-stack development
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I hold a Ph.D. degree in biophysics from Rice University with a focus in gene expression network analysis and neural network analysis. I developed models to study how biological structure spontaneously arises in an evolving system. After Ph.D. I worked as a data engineer at Two Sigma Investments,I built tools to automatically acquire, process and visualize financial data and maintained database used for trading and research.
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Choudhary Anshul Choudhary, Ph.D. |
Farmington, CT |
Uncovering temporal dynamics of large collection of cells by applying machine learning and dynamical systems framework to single cell sequencing data.
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I'm a computational scientist working at the intersection of genomics, machine learning and nonlinear dynamics in advancing data-driven scientific discovery. Specifically, I'm developing a novel based approach whereby RNA velocity is used to further dissect a purely expression-based clustering using ideas of attractors and basins in dynamical systems. In another direction, I'm also working on developing an integrated mouse phenotyping platform that is an end-to-end solution to data collection, automated behavior quantification using machine learning and downstream genetic analysis for the laboratory mouse.
I earned my PhD in physics focusing on the mathematical modeling of dynamical systems (deterministic and stochastic differential equations) on graphs (complex network topologies) to study the emergence of rich spatio-temporal patterns in various complex systems spanning from physics to ecology. After PhD, I did my first postdoc in the theoretical ecology group at the Institute for chemistry and biology of marine ecosystems in Germany, where I worked on developing mathematical models of biodiversity in multi-species ecosystems competing for limited resources and developed expertise in applying machine learning methods to learn species-species trait relationships. Subsequently, I took a second postdoc at NC state university where I worked on the design and implementation of physics aware neural networks that can learn to correctly predict the dynamics of a system while respecting the underlying conservation laws. I also worked a bit on design of latent models that would enhance the interpretability and explainability of models in scientific machine learning.
At JAX, I'm excited to work on predicting cell fate dynamics by constructing a transcriptome-wide continuous vector field from RNA velocity.
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Anshul Choudhary on ORCID
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Lab Staff |
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Davis Sara Davis, MA |
Farmington, CT |
Working collaboratively to understand and solve for users' needs.
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After receiving my degree in Museum Studies in 2010, I moved to St. Louis, MO to work at the Saint Louis Science Center as an exhibits and program evaluator. In 2018, I participated in a museum conference that changed my career trajectory by introducing me to human computer interaction concepts. I later found a bootcamp program for user experience design which then connected me to my first job as a UX designer. I joined CS in August 2022 and primarily design for BioConnect, but I also enjoy working collaboratively to increase usability across all CS applications.
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Lab Staff |
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Desai Sejal Desai, B.S. |
Farmington, CT |
“Quality is not an act, it is a habit.”— Aristotle. I am passionate about testing and validating software systems that help solve problems and work with my team to ensure that a quality product is delivered .
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I hold Bachelors in Electronics Engineering and I have over 18 years of experience in Software Testing and validation. I have been involved with testing real time systems and complex integrated systems. I have led testing teams in various industrial domains such as E-Commerce, Oil and Gas, Nursing education and storage and network controller testing. This has helped me develop an insight to looking at applications from design as well overall system perspective. I love to work with my team at The Jackson Laboratory to develop and deliver quality software which helps scientific community in their research efforts to make a difference in biomedical world!
Download CV
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Software Engineer |
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Domanskyi Sergii Domanskyi, Ph.D. |
Farmington, CT |
Development of novel computational, statistical and mathematical approaches for the analysis of Next Generation Sequencing (NGS) data.
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I have a strong background in the physical and computational sciences, large-scale computational techniques, and software design, allowing me to model biological systems in multidisciplinary projects.
In my post-doctoral research at Michigan State University, I have developed novel statistical and mathematical approaches in open-source packages PyIOmica, DigitalCellSorter, and DECNEO for time-series data analysis and discovery of the combinations of receptors from an extensive collection of single-cell RNA sequencing datasets. Currently, I am developing advanced computational approaches for quality control and downstream analysis of spatially resolved transcriptomics data. I am interested in algorithms exploring tumor growth, development dynamics, and gene expression regulation. I enjoy researching complex processes in the tumor microenvironment to help understand cancer biology questions through the analysis of Next Generation Sequencing data. I help automate and standardize data analysis workflows by creating Nextflow-based computational pipelines using state-of-the-art computational biology methods. My objective is to continue biostatistics analysis, develop bioinformatics algorithms and encapsulate these novel methods in reliable software for personal and HPC systems..
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Visit Personal Lab Site
Sergii Domanskyi on ORCID
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Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
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Dunn Matthew Dunn, B.S. |
Bar Harbor, ME |
Creating software to help scientists analyze and visualize large data sets, with a focus on data intake and curation.
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I worked as a programmer on medical software for 6 years, where I gained a strong background in software development. When a bug could negatively impact the health of a patient, it really impresses upon you the importance of attention to detail, testing, and writing bug-free, supportable, and well-documented code.
Since joining JAX in June of 2017, I have mostly been working on the Mouse Phenome Database (MPD) website, and as the primary developer on the data intake and curation website, Study Intake Platform (SIP). I am a full stack developer, working on user interfaces (including data visualizations and data entry forms), backend RESTful APIs, database maintenance and migrations, VM server management, and migrations to cloud-hosted environments. My primary development tools: Languages – Python, JavaScript, Typescript; Web development – Flask, Flask-RESTX, Angular; Visualization - D3 & Highcharts; Database – PostgreSQL; Cloud – GCP.
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Behavioral Disorders|Bioinformatics|Computational Biology|Genetics and Genomics |
Behavioral Disorders|Bioinformatics|Computational Biology|Genetics and Genomics |
The Chesler Lab |
Alumni|Software Engineer |
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El Kassaby Baha El Kassaby, MSc |
Bar Harbor, ME |
Areas of interest include machine learning, data analysis, image analysis, and data mining. Particularly interest in how to best apply standard/industry software engineering practices to scientific research software projects.
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I'm interested in how to leverage open-source software to help advance scientific research. An active contributor to open-source projects, I contributed to the development of data analysis tools used in synchrotron experiments. As a member of the Computational Science team at JAX, I am working on full-stack applications using Angular, Python, Java and R.
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Baha El Kassaby on Research Gate
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Computational Biology|Genetics and Genomics|Bioinformatics |
Computational Biology|Genetics and Genomics|Bioinformatics |
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Emerson Jake Emerson, M.S. |
Bar Harbor, ME |
As a software engineer I build fast, reliable systems that solve hard problems. I am also interested in causal reasoning, information theory, and logic.
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My professional career started in the US Army Corps of Engineers. While stationed in Alaska, the Marshall Islands, the Republic of Korea and Iraq, I worked as a construction engineer, project manager, explosives and demolitions trainer, and logistics officer. After military service, I have been involved in both the worlds of startups and academia. I have led projects in a variety of fields including: hydrologic warning, field maintenance operations, crisis informatics, oceanographic event analysis, and software development. I have also been an assistant instructor in the Department of Spatial Information Science and Engineering at the University of Maine.
I hold a B.S. in mechanical engineering from the U.S. Military Academy at West Point, and a M.S. in environmental engineering from the the Missouri University of Science and Technology.
Jake Emerson on ORCID
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Bioinformatics|Complex Traits|Computational Biology |
Bioinformatics|Complex Traits|Computational Biology |
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Computational Scientist|Software Engineer |
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Ferraj Ardian Ferraj, Ph.D. |
Farmington, CT |
My research interests include the application of next generation sequencing and genomic data to answer complex biological questions.
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My doctoral research included studying the impact of large genetic variants on diverse genomes, focusing on the effects of mobile element insertions on stem cell transcription. In my current work, I employ advanced sequencing technologies to study tumor-stroma interactions of patient derived xenograft models in cancer therapy.
Ardian Ferraj on Orcid
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Lab Staff|Predoc |
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Fields Peter Fields, Ph.D. |
Farmington, CT |
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In my current role and throughout my research career, I have worked at the cutting edge of high throughput sequence data, bioinformatic analysis, and population genomics to answer research questions in evolutionary biology. In my present position I have a particular focus on the application of long-read sequencing technologies and on the transitioning of analysis methodologies from single, linear reference genomes to genome graphs.
Peter Fields on ORCID
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Computational Scientist |
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Frohock Zachary Frohock |
Bar Harbor, ME |
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Before coming to JAX, I collected a bit experience in a small variety of fields. My education is in Physics, specializing in the imaging of novel magnetic materials. In particular, I explored the application of yttrium iron garnet as a read/write medium in high temperature hard disk drives. I spent time with a few data science startups; one that performed analysis to detect oil pump suboptimal performance and failure, and another which provided a platform for automated data shaping. My work at JAX consists of applying deep learning methods to image data. From mouse brain MRIs to 3D multiplexed immunohistochemistry images, I seek to extract valuable insights via research and streamline workflows such that scientists are better able to apply their skills where they can make the most difference via software development.
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Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
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Bioinformatics/Data Analyst |
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Gargano Michael Gargano, B.S. |
Farmington, CT |
Here to make a difference in translational genomics and the clinical world.
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I am a software engineer working to make a difference where biology and computer science meet. I excel in full-stack web applications, bioinformatics, and delivering stable products. I aim to bridge the gap between translational genomics and user experience.
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Behavioral Disorders|Bioinformatics|Cancer|Computational Biology |
Behavioral Disorders|Bioinformatics|Cancer|Computational Biology |
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Software Engineer |
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Gatti Daniel Gatti, Ph.D. |
Bar Harbor, ME |
Developing statistical and computational techniques that use genetic diversity to help researchers answer biological questions.
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I earned my Ph.D at the University of North Carolina at Chapel Hill in the toxicogenomics lab of Ivan Rusyn, where I studied the effects of genetic diversity on gene expression. I then worked at the Jackson Laboratory in Gary Churchill's group, where I developed and applied analytical methods for genetically diverse mice. I developed the first tools for haplotype reconstruction and genetic mapping in Diversity Outbred (J:DO) mice and have been involved in many projects that use J:DO mice. I currently work on tools and educational materials to help investigators use genetically diverse mice in their research.
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Daniel Gatti on ORCID
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Aging|Bioinformatics|Complex Traits|Computational Biology |
Aging|Bioinformatics|Complex Traits|Computational Biology |
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George Joshy George, Ph.D. |
Farmington, CT |
My research focuses on applying machine learning, statistical techniques, and computational methods to address problems ranging from experimental design to data analysis in systems biology.
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My interest is to develop principled methods to solve biological problems using quantitative methods from bioinformatics, machine learning, data science, and mathematics. In our group, we apply these computational methods to build predictive models to support cancer precision medicine and to understand the molecular mechanisms leading to diseases.
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Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
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Gerring Matthew Gerring, MEng |
Bar Harbor, ME |
My interests are in making scientific algorithms reproducible, able to run at scale and have an ergonomic user interface which give value to a wide community in science.
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Since 1998 I have been developing scientific software, for instance computational fluids dynamics on desktop and the web and data acquisition and analysis at the UK's largest science project (Diamond Light Source). At JAX I have been working with Chesler Lab to create a graph database which maps genetic information between humans and mice. Recently I have been working moving image analysis software to the cloud. Scientific software development is where my heart is and what makes the most interest for me at work.
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Matthew Gerring on Researchgate
Visit Dawn Science
Visit Geneweaver
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Aging|Behavioral Disorders|Cancer|Diabetes and Obesity |
Aging|Behavioral Disorders|Cancer|Diabetes and Obesity |
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Lab Staff|Software Engineer |
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Grubb Stephen Grubb, M.S. |
Bar Harbor, ME |
I help to develop web applications, workflows and databases in domains such as iPSC cell line & CRISPR informatics, cancer tumor sample variants and genomics, murine phenotyping and genotyping, colony management/tracking, and interoperability with bioinformatics APIs, ontologies, and other resources.
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Originally from the mid-Atlantic region I worked in clinical trials data management and GDB/OMIM at Johns Hopkins, worked overseas in west Africa and Jamaica for several years, then joined Jax in 2000 as a founding developer of the Mouse Phenome Database, later diversifying to other Computational Sciences projects. I'm active in several community organizations and music groups in Bar Harbor.
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Software Engineer |
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Harder Jeffrey Harder, Ph.D. |
Bar Harbor, ME |
Biomedical scientist interested in uncovering the interactions between genes and environment that dictate the occurrence and form of disease.
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I have a background in research and model development in glaucoma, diabetes, and COVID-19. My current interests include using single cell and spatial transcriptomic technologies to investigate disease mechanisms and improving translation of animal research using genetically diverse models and cross-species analyses.
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Genetics and Genomics|Bioinformatics|Computational Biology|Diabetes and Obesity |
Genetics and Genomics|Bioinformatics|Computational Biology|Diabetes and Obesity |
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Computational Scientist |
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He Hao He, Ph.D. |
Farmington, CT |
Multi-omics (e.g. genomics, transcriptomics, epigenomics, proteomics, etc.) and data integration, Biostatistics and Bioinformatics, Data science, statistical learning and visualization
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I hold a Ph.D. degree in Biostatistics from Tulane University. My research mainly focuses on developing and applying computational and statistical approaches to integrate and interpret large-scale biological “omics” data, with the goal of identifying disease mechanisms, biomarkers and treatment targets..
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Cancer|Computational Biology|Complex Traits|Bioinformatics |
Cancer|Computational Biology|Complex Traits|Bioinformatics |
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Kadakkuzha Beena Kadakkuzha, Ph.D. |
Bar Harbor, ME |
Find personalized solutions for diseases.
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I hold a Ph.D. in Molecular Biology from the University Texas at Dallas and postdoctoral training in functional genomics and transcriptomics from The Scripps Research Institute, Jupiter, Florida. I transitioned from a research scientist to the field of research project/program management and at JAX, I am part of a robust team of faculty, software engineers, computational scientists, bioinformaticians, and statistical analysts at the Computational Sciences (CS) department whose mission is to provide the informatics resources and services to JAX’s faculty to conduct research of the highest scientific merit. As a Research Project Manager, I facilitate agile project management approaches to plan, facilitate, execute, and deliver software applications, tools, and platform to solve complex problems in genetics and genomics.
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Behavioral Disorders|Bioinformatics|Cancer|Computational Biology |
Behavioral Disorders|Bioinformatics|Cancer|Computational Biology |
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Kayastha Sneta Kayastha, MS |
Farmington, CT |
My work focuses on streamlining DevOps processes in medical research, emphasizing robust infrastructure, continuous integration, regulatory compliance, data privacy and security.
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I have a M.S in CIS&IT from University of Central Missouri followed up with years of IT experience working in Healthcare and Telecommunication industries as Developer and DevOps Engineer. As a DevOps engineer in Jax, my primary responsibility is to bridge the gap between development and operations teams to ensure the seamless development, deployment, and maintenance of research software and infrastructure. I play a crucial role in automating processes, optimizing workflows, and enhancing the reliability and systems.
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Computational Scientist |
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Khan Taushif Khan, Ph.D. |
Farmington, CT |
Computational biologist interested in understanding immune response and regulation profiles in the context of diseases and genetics.
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My research has focused on immune-genetics and immune-regulation at a resolution of both population and patient-driven questions. I used high dimensional biological data from WGS and functional immune profiling and applied multi-omics approaches by integrating data from RNA-Seq, PhIP-Seq and microbiome data. I am highly interested in building & deploying statistical models to understand biological patterns.
Taushif Khan on ORCID
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Bioinformatics|Computational Biology|Genetics and Genomics|Cancer |
Bioinformatics|Computational Biology|Genetics and Genomics|Cancer |
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Computational Scientist |
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Kolishovski Georgi Kolishovski, M.S. |
Bar Harbor, ME |
I am interested in high performance computing, statistical analysis, and biological systems modeling.
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My primary focus at JAX is on developing data management systems and tools for the exploration and visualization of complex biological data and its interpretation. As part of a multidisciplinary team at JAX, I frequently collaborate with both experimental and computational scientists on data analysis and visualization projects.
In my role as a Scientific Software Engineer, I am leading the JAX Synteny Browser, a novel tool for interactive visualization of regions of conserved synteny between two genomes based on their biological properties such as function and phenotypes.
Another hallmark initiative that I am closely involved in is JAX’s Patient–Derived Xenografts (PDX) program, a platform for data management, visualizations, analysis, reporting of cancer models studies. I lead the implementation of interactive visualizations for cancer treatment response studies (SOC) and develop automated software to run robust pipelines for the analysis of genomic variations in cancer models.
I am also a key member of the Mouse Phenome Database (MPD) project, an integrated platform to explore physiology and behavior through genetics and genomics, for which I create highly interactive data visualization tools using the latest cutting edge and open source technologies.
In addition, I also teach several data science and programming courses/workshops at JAX on coding skills in R, Python and SQL.
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Data Science at The Jackson Laboratory |
Data Science at The Jackson Laboratory |
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Software Engineer |
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Kostich Mitch Kostich |
Farmington, CT |
Application of computational statistics and machine learning to high-dimensional biological and chemical datasets. Software development and high-performance computing.
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My doctoral work focused on vertebrate cell biology, but relied on genomic sequence analysis to identify a more tractable homolog of an ostensibly vertebrate-specific gene in C. elegans. I subsequently worked in the pharmaceutical industry on identifying potential drug targets, comparative genomics, RNA sequence assembly, and bulk annotation of sequence data. Later, as a researcher at USEPA, I identified transcriptomic signatures of exposure to various toxicant classes, developed predictive models for chemical risk assesment and worked on computational tools for contaminant screening using time-of-flight mass spectrometry. Since joining JAX, I have been leading small teams of computational scientists and software engineers, as well as developing pipelines for long-read sequence analysis and splice-variant analysis. I have also taught short courses on various aspects of applied statistics, machine learning, software development and bioinformatics.
Mitch Kostich on ORCID
Mitch Kostich on Google Scholar
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Computational Scientist |
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Lek Sai Lek |
Farmington, CT |
Bioinformatics, Cloud/High Performance Computing, Pipeline Development, Microbiome, Cancer biology, Precision Medicine, Genetics, and Genomics
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I hold a M.S. in Computer Science with a background and hands on experience in High Performance Computing, Analysis Pipeline Development, Genome Assembly & Annotation, Microbiome Data Analysis, Long-Read Sequencing (PacBio & Oxford Nanopore). Previously I worked in The Genome Institute (Washingtion University School of Medicine in St. Louis), The Weinstock Lab and Microbial Genomic Services at JAX. I am now a member of Computational Sciences and working on Pipeline developments & Microbiome related projects.
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Lab Staff |
Associate Director of Machine Learning & Imaging Services
Farmington, CT
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Li Yi Li, Ph.D. |
Farmington, CT |
Integrative analysis of multi-omics data; integrative cross-species analysis of multi-omics data; AI and machine learning method development for and applications to bio-medical fields; image analysis.
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My overall goal is to apply and develop computational tools that analyze biological data to better understand the mechanisms of complex diseases, with a particular focus on AI and machine learning methods. As the Associate Director of Machine Learning & Imaging, Computational Sciences, The Jackson Laboratory, I strive for deep understanding of the most recent machine learning theories and development and identifying their applications in biomedicine, as well as developing new methods for improved analysis. I participated in the MODEL-AD project during the past five years which aims to develop and evaluate various mouse models for human late onset Alzheimer’s disease (AD). When I applied deep learning methods to extract MRI image features and linked them to genetics and metabolites for an AD study of the MODEL-AD project, I realized existing tools are insufficient to enable us to know which mouse strains best reflect the AD mechanisms in human. Hence, my group recently developed a graph neural network-based cross-species gene expression data analysis framework that aims to maximize the similarity between mouse disease models and human disease data. The longer-term goal of my group is to develop an expandable AI framework for cross-species analysis of multi-omics data which not only include genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiome data, but also images, including cell images, MRI, fMRI, DTI, CT and multiplexed tissue images.
I have published more than 45 peer-reviewed papers in various journals, including first or co-first author publications in Nature Genetics, American Journal of Human Genetics, Machine Learning, Journal of Computer and System Sciences, and IEEE Transactions on Information Theory.
Download CV
Yi Li on Google Scholar
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Bioinformatics|Complex Traits|Genetics and Genomics|Neurodegenerative and Neuromuscular Diseases |
Bioinformatics|Complex Traits|Genetics and Genomics|Neurodegenerative and Neuromuscular Diseases |
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Liang Hongping Liang, Ph.D. |
Farmington, CT |
Designing, building, and maintaining the infrastructure that supports data storage, processing, and retrieval (FAIR) in premise and on cloud for large volume biological data.
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I have an unique background of PhD in biology and MS in computational science. I am AWS certified solution architect and Hortonworks certified developer, and have two decades of experience in big data, cloud, application design, development, and deployment. My current projects leverage GCP Cloud storage and BigQuery to curate our ATAC_seq, RNA_seq, single cell, and SNP/variant data. I build various ETL tools to load, process, analyze these data, and design and develop applications for scientists to access these data from web and through HPC environment.
Hongping Liang on Orcid
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Computational Scientist |
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Liedtka Camille Liedtka, BA, MS |
Bar Harbor, ME |
Agile project management methodologies, Knowledge Services, Organizational Behavioral Analysis, Public Health, Anthropology.
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Camille Liedtka has a background in medical Anthropology and Behavioral Analysis and is pursuing a master’s degree in Project Management at Northeastern University. She is currently working at Jackson Labs as an Associate Research Project Manager with the Computational Sciences team where she leverages agile methodologies and workflows to allow for projects to match the pace of innovation. Previously she worked at Wayfair as a customer service trainer where she wrote, developed and facilitated curriculum while leading international project teams focused on knowledge services & distribution.
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Lab Staff |
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Lloyd Michael Lloyd, Ph.D. |
Bar Harbor, ME |
My research has focused on the application of genetic data to complex biological problems.
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I joined the Jackson Laboratory having previously worked on a diverse set of organisms. My Ph.D. focused on population and conservation genetics of a submersed aquatic plant species, which was targeted for restoration efforts. Prior to joining Jax, I was a member of the Department of Entomology at the Smithsonian Institution. In that role, I was responsible for the generation and analysis of target enrichment data used in phylogenomics. At Jax I have been involved in research projects associated with the Jax PDX program, PDX Network, PIVOT consortium, and Cube initiative.
Michael Lloyd on ORCID
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Computational Scientist |
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Mahoney Matt Mahoney, Ph.D. |
Bar Harbor, ME |
Machine learning for complex trait analysis.
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I am a mathematician with a wide range of interests in systems biology. My current research focuses on machine learning tools to automatically identify biologically meaningful phenotypes from high-dimensional signals (e.g., molecular signatures, images, or time series) and gene prioritization for gene mapping experiments. I am currently a core leader for image analysis in the JAX Senescence Network Mouse Tissue Mapping Center and the Shock Center for Excellence in Aging Research. I am also interested in genetic network analyses and causal modeling for complex biological data.
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Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
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Mawe Seamus Mawe, B.A. |
Bar Harbor, ME |
High Throughput Image analysis of histological data.
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My B.A. from the University of Vermont is in Pure Mathematics. I joined Jax Computational Sciences in 2020 as a Research Assistant and became a Research Data Analyst in 2022. My primary area of expertise is in image analysis using deep neural networks in Python and Julia with a focus on histological images. I am currently pursuing an M.S. in Data Science from the Roux Institute at Northeastern.
Seamus Mawe on ORCID
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Miller Abigail Miller, B.S. |
Bar Harbor, ME |
Designing and developing software systems to improve the capture and storage of laboratory data, especially as it applies to laboratory workflows.
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Broad experience working with animal model based LIMS systems, including UI design, system architecture and integration, data modeling, and development. When I started at Jax in 2003, I worked for Dr. Carol Bult in the NMF on the JaxTrack system supporting colony management and phenotyping. I subsequently joined Computational Sciences, where I worked on the JCMS and JaxLIMS systems. I spent a few years away from Jax working on a commercial SaaS LIMS system, primarily responsible for system architecture and DevOps. This gave me the opportunity to work with a large number of academic and commercial laboratories doing animal model research, and allowed me to participate in Microsoft engineering workgroups and case studies. I am excited to be back as a software engineer in Computational Sciences and look forward to working on the Cube initiative.
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Motakis Efthymios Motakis, Ph.D. |
Farmington, CT |
Statistics, Biostatistics, Computational Biology, Statistical Methods Development, Software Development (R packages)
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I joined the Jackson Laboratory in 2020 as a Computational Scientist. I am focusing on the statistical analysis of single cell omics and the development of methods for data normalization, variance stabilization, differential expression and image processing. Prior to the Jackson Laboratory, I was a Senior Research Fellow at the Cardiovascular Research Institute of the National University of Singapore. Before that, I was employed in RIKEN Yokohama and in the Bioinformatics Institute of Singapore as a senior researcher. I received my Ph.D. in Statistics from the University of Bristol, UK in 2008.
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Efthymios Motakis on ORCID
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Aging|Bioinformatics|Cancer|Computational Biology |
Aging|Bioinformatics|Cancer|Computational Biology |
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Paisie Carolyn Paisie, Ph.D. |
Farmington, CT |
My research interests are in bioinformatics, cancer biology, genetics, and genomics.
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I received my PhD in Integrated Biomedical Science, concentration in cancer biology, from Ohio State University and my MS in Biomedical & Health Informatics from University of Washington. During my PhD, I focused on mouse genetics and genomics from the perspective of a bench scientist; my dissertation work involved investigating mutation types and numbers in preneoplastic cells and tissues from Fhit knockout mice. I completed a postdoctoral fellowship and MS degree simultaneously at the University of Washington where I investigated differential gene expression in the parasite Leishmania donovani.
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Computational Biology|Bioinformatics|Cancer|Genetics and Genomics |
Computational Biology|Bioinformatics|Cancer|Genetics and Genomics |
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Bioinformatics/Data Analyst |
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Park Juno Park, BS |
Bar Harbor, ME |
Specializing in research and development, I seek to design and develop software solutions for complex datasets and abstract problems.
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After obtaining my B.S. in Electrical Engineering and Computer Sciences at the University of Maine in May 2021, I began working as an Associate Scientific Software Engineer on the Computational Sciences team. My time thus far at JAX has been spent developing the BioConnect project. I work as a research and development engineer, seeking to find creative solutions to complex datasets and problems. My experience includes UI design, data modeling, web app design & development, and data visualization. My back-end experience is varying due to my Electrical Engineering background, but I'm working towards becoming a full-stack engineer.
I'm looking forward to expanding my knowledge at JAX and being a part of the Cube Initiative.
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Software Engineer |
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Philip Vivek Philip, Ph.D. |
Bar Harbor, ME |
My interests lie in the application of statistical methodologies to the area of genetics, specifically quantitative trait genetics and genomics for hypothesis generation and validation.
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I hold a PhD in Life Sciences from University of Tennessee/Oak Ridge National Laboratory Genome Science and Technology Program, with a focus in statistical and quantitative trait genetics of behavioral traits in genetic reference populations and integrative functional genomics of behavior across species and experimental platforms. During my Ph.D. program I investigated the increased precision and resolution in QTL mapping using mouse reference populations including the expanded BXD recombinant inbred (RI) strain panel and the Collaborative Cross (CC) reference population The BXD RI study highlighted the increase in statistical power obtained in using the expanded BXD RI strain panel. The CC study highlighted the increased allelic variation and QTL mapping precision achieved. Upon completion of my Ph.D., I joined the Computational Sciences - Statistics and Analysis group at The Jackson Laboratory in 2012 as a biostatistician, with responsibilities including QTL analysis, expression QTL analysis, gene expression analysis, statistical modeling of diverse biological datasets, and statistical consulting. In addition to my contributions towards the field of quantitative trait genetics and statistical genetics, I have undertaken several other data analysis tasks involving differential gene expression analysis using next generation sequencing technologies, leading to the generation of new or validation of existing hypothesis.
For a complete list of my published work, please visit my NCBI bibliography.
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Behavioral Disorders|Bioinformatics|Complex Traits|Computational Biology |
Behavioral Disorders|Bioinformatics|Complex Traits|Computational Biology |
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Director |
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Poirion Olivier Bertrand Poirion, Ph.D. |
Farmington, CT |
Applies bioinformatics and machine learning algorithm methodologies to explore high-dimensional genomic datasets with an emphasis on single-cell and survival analyses.
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Over the past ten years, I specialized myself in big data analysis (i.e., Machine-Learning) applied to Genomics, Semantics and Next Generation Sequencing (NGS) data linked to single-cell and cancer research. I obtained my PhD in Computational biology and Evolutionary Genomics at Ecole Centrale de Lyon (Lyon University), France. My previous research at the Cancer Center of the University of Hawaii and the Center for Epigenomics (UCSD) elaborated advanced analytical methods and workflows for single-cell, multi-omics, and survival datasets. My current work involves working with single-cell ATAC-Seq and RNA-Seq datasets and developing new statistical methods for inferring epigenomics regulation.
Olivier Poirion on ORCID
Oliver Poirion on Google Scholar
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Bioinformatics|Computational Biology|Genetics and Genomics |
Bioinformatics|Computational Biology|Genetics and Genomics |
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Saul Michael Saul, Ph.D. |
Bar Harbor, ME |
Using computation, genetics, and genomics, I study neurobiology and behavior.
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My perspective on biology celebrates what diversity can teach us. Within the mouse species, I study genetically diverse populations such as the BXD, Collaborative Cross, and Diversity Outbred. With Elissa Chesler and colleagues in the CSNA, my work has reiterated that who a mouse is – their genetic makeup and its sex – matters greatly to how a mouse behaves and how their brain responds. I am particularly interested in comparative and cross-species techniques, which give us perspective on the conserved systems that underpin similar behaviors spanning the animal kingdom.
Though I now work in Computational Science, my training was as a mouse behavioral neuroscientist who studies genetics and genomics. My work convinced me that biologists must do two things to understand complex systems like the brain: 1) collaborate with each other, and 2) use high-throughput techniques like next-generation sequencing and high-performance computing. I am delighted to collaborate with multiple investigators at JAX, where I apply the skills I attained in computational work to find the new biology of disease that will lead us to better treatments.
Michael Saul on ORCID
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Aging|Behavioral Disorders|Bioinformatics|Complex Traits |
Aging|Behavioral Disorders|Bioinformatics|Complex Traits |
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Computational Scientist |
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Sebasco Nick Sebasco, MS |
Bar Harbor, ME |
I am interested in working on software development projects involving applied mathematics, computer vision, and machine learning.
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I received my MS in mathematics and wrote my thesis on graph based image segmentation. I like to work on mathematical machine learning algorithms and optimization problems. I plan to develop and implement state of the art algorithms to solve high impact genomics problems.
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Aging|Cancer|Computational Biology |
Aging|Cancer|Computational Biology |
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Software Engineer |
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Skelly Daniel Skelly, Ph.D. |
Bar Harbor, ME |
Biologist and data scientist harnessing single cell functional genomics and genetically diverse mice to study complex traits
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Variation in observable traits, such as disease susceptibility, is pervasive in the natural world. Recent advances in sequencing and computation are providing us with an unprecedented view of patterns of genetic variation within species. A major outstanding challenge is to identify and characterize the specific genetic variants affecting complex traits, and the mechanisms through which they do so.
I am a biologist and data scientist who uses single cell functional genomics to understand the genetic basis of complex traits. I utilize genetically diverse model organism populations together with the methodology of statistical and quantitative genetics to reveal novel mechanistic insights into the biology of complex traits. My background and interests include cancer, cardiovascular disease, diabetes, and obesity/metabolic disorders.
Daniel Skelly on Google Scholar
Daniel Skelly on ORCID
Visit Personal Lab Site
Download CV
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Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
The Rosenthal Lab |
Research Scientist |
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Somarakis Antonios Somarakis |
Farmington, CT |
Analysis and pipeline development of spatial proteomics and trascriptomics data employing machine learning techniques.
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My project focuses on the analysis of spatial single-cell proteomics data (e.g. Imaging Mass Cytometry, CODEX) and spatial transcriptomics data (e.g. Visium Spatial Gene Expression by 10x). Previously, in collaboration with biologists from Leiden University Medical Center I have developed interactive pipelines for the analysis of single-cell high-resolution images (ImaCyTe, SpaCeCo). My research interests also include the analysis of single-cell tissue images with Graph Convolutional Networks.
Antonios Somarakis on ORCID
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Bioinformatics|Cancer |
Bioinformatics|Cancer |
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Computational Scientist |
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Stafford Grace Stafford, Ph.D. |
Bar Harbor, ME |
Analyzing and structuring data to facilitate research and break down silos.
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I joined The Jackson Laboratory's Computational Sciences Department to become the Deployment Lead in the Lab’s involvement in the NCI Cancer Biomedical Informatics Grid® (caBIG®) initiative and stayed on as a member of the Stats and Analysis group. My background in protein and genomic databases and conceptual representations of life sciences research has enabled me to contribute to the clinical and the PDX programs. I continue to gain experience in analysis of next generation sequencing, calling on my history of bench research in cancer, pharmacology, and transcriptional regulation. I have experienced the roller coaster ride of small start up companies and welcome the opportunity to be part of the JAX community. On any given day, I may spend time wrangling data for PIs or collaborators, launching a DNA-seq analysis, tracking down data for a potential PDX customer and checking out a new analysis tool or online database.
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Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
Bioinformatics|Cancer|Computational Biology|Genetics and Genomics |
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Bioinformatics/Data Analyst |
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Stearns Timothy M. Stearns, B.S., M.S. |
Bar Harbor, ME |
Leveraging the use of statistics and computational resources to reveal the genetic basis for disease.
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My initial contributions to science were the result of a Master of Science education program (University of Illinois - Champaign-Urbana) endeavor to identify quantitative trait loci affecting swine meat characteristics. Shortly after my leave of the University, I joined The Jackson Laboratory in 2007. The numerous collaborations that took place at the Laboratory have resulted in publications pertaining to a variety of conditions including: alopecia areata, asthma, cancer (of the brain, lung and skin), diabetes, chronic kidney disease, eye disease, and reproductive disorder. The general aim of these studies is to provide mouse model information as a method to improve human health. My role in these studies has been as a biostatistician consultant.
For a complete list of my published work, please visit my NCBI bibliography.
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Biostatistician |
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Sundberg Beth Sundberg, M.S. |
Bar Harbor, ME |
Design and develop relational databases; software quality assurance testing.
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Ms. Sundberg has been involved with computer applications for 45 years. She developed herd health management software in 1976, a database for managing pesticide chemicals for the state of Indiana in the mid 1970s, and worked on various other projects for the Administrative Data Processing Center at Purdue University. During the past thirty years she has worked on a project for managing mouse breeding colonies (JAX Colony Management System, JCMS) and a relational database for medical records management (The Mouse Disease Information System, MoDIS). MoDIS was developed in 1987 to manage histopathological data from The Jackson Laboratory massive mouse production colony as well as research data. Over the years this evolved to integrate the Mouse Anatomy Ontology (MA) and Mouse Pathology Ontology (MPATH), to eventually provide an integrated tool for storage of basic research discoveries, linking gross and photomicrographs to case materials, and getting this information into publicly accessible databases such as Pathbase (http://www.Pathbase.net), and Mouse Genome Informatics (http://www.informatics.jax.org). Currently she is providing software quality assurance for these Computational Science projects: PDX (patient-derived xenograft) platform, GeneWeaver, BioConnect, Mouse Phenotype Database (MPD), Study Intake Platform (SIP), Diversity Informatics Platform (GeDI), POET, and PhenoPackets. .
Visit JAX Colony Management System (JCMS)
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Computational Biology |
Computational Biology |
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Software Engineer |
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TeHennepe Gregg TeHennepe, B.A. |
Bar Harbor, ME |
Leading the advancement of data science capabilities to accelerate research, discovery, and innovation.
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I am 30+ year technology and research management professional with experience in leading complex programs and initiatives in the life sciences. My knowledge of strategic program leadership, research project management, information technologies, molecular biology and genetics combine with outstanding communication, analysis and collaboration skills to enable transformative team data science.
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Bioinformatics|Genetics and Genomics|Resource Development and Dissemination |
Bioinformatics|Genetics and Genomics|Resource Development and Dissemination |
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Associate Computational Scientist
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Tripathy Rohit Tripathy |
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I work on integrative cross-species data analysis and explainability of deep learning models in genomics.
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I am primarily trained as a computational scientist. During my Ph.D., I worked on the developing probabilistic machine learning methodologies for various computational problems in engineering systems (uncertainty quantification, stochastic partial differential equations, dynamical systems, inverse problems etc.). As a postdoc, I worked on the problems pertaining to the interpretability of sequence-function relationships learned by DNN models from high-throughput sequencing functional assay datasets. As a computational scientist at JAX, I work on integration of cross-species and multi-omics data.
Rohit Tripathy on ORCID
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Computational Scientist |
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Walton Benjamin Walton, B.S. |
Bar Harbor, ME |
Interested in building intuitive applications and data visualizations to aid scientific research.
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As a Scientific Software Engineer, I help make biological data easier to manage and interpret. I have a B.S. in Bioengineering from the University of Maine which gave me a strong foundation in biology with a technical perspective. After spending a few years at a biotech software startup in Portland, I'm excited to bring everything I've learned to JAX where I hope to contribute to a variety of important projects.
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Computational Biology|Genetics and Genomics |
Computational Biology|Genetics and Genomics |
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Computational Scientist |
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Walton Dave Walton, B.A. |
Bar Harbor, ME |
Primary focus is developing scientific software tools to further the research of Jackson Laboratory faculty.
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I am a full-stack principal level scientific software developer with a passion for software development that enables scientific research. I have over two decades of experience in a variety of industries, with a focus in biotechnology.
My primary Development tools: Languages – Python, Java, Groovy, JavaScript; Web development – Flask, FastAPI, Angular; Visualization - D3 & Highcharts; Database – PostgreSQL, MySQL, Oracle, Mongo, Neo4j; Cloud – GCP. I have worked on large scale enterprise LIMS for collecting, tracking, processing and reporting patient samples; command-line analysis tools for scientific data; web applications for the presentation of analyzed results; and API’s to allow other programs access to data and tools using RESTful web services and JMS.
My role at Jackson Laboratory is one of technical leadership on multi-developer projects, using agile techniques, striving to provide meaningful/usable systems in a timely manner.
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Software Engineer |
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White Brian White, Ph.D. |
Farmington, CT |
Applies statistical modeling and machine learning to elucidate the impact of tumor and patient heterogeneity on disease outcome and therapeutical response.
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Emerging single-cell transcriptomic and highly-multiplexed imaging methodologies are advancing our basic understanding of tumor heterogeneity and its impact on patient outcome and therapeutic response. My previous work involved predicting disease progression and drug response using bulk (principally, expression) data. My interests lie in leveraging these new single-cell modalities to improve our ability to extract insight from the wealth of existing (and clinically annotated) bulk data. For example, we have recently completed a deconvolution DREAM challenge comparing methods that infer immune sub-populations from bulk expression data. Several participant methods used single-cell RNA-seq to identify markers that could subsequently be used to detect the corresponding population in bulk data.
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Brian White on ORCID
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Bioinformatics|Cancer|Computational Biology |
Bioinformatics|Cancer|Computational Biology |
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Yu Miao Yu, Ph.D. |
Farmington, CT |
My research interest is high resolution mass spectrometry based data analysis and applications in 'omics' study.
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My research is focused on the mediation roles of molecular between exposures and health outcomes. I developed PMDDA data analysis workflow to perform exhaustive metabolomics annotations. I also proposed the concept of 'reactomics' to retrieving general chemical relationships among molecular in biological samples. Meanwhile, I developed 'gatekeeper' model to screen the molecular sensitive to multiple exposures. With background from both wet lab and dry lab, I am trying to improve regular statistical or machine learning model with biochemistry knowledge. I am also interested in reproducible research and built a R based data analysis image (xcmsrocker) for reproducible metabolomics data analysis.
Miao Yu on ORCID
Miao Yu on Github
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Bioinformatics|Computational Biology |
Bioinformatics|Computational Biology |
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Computational Scientist |
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Yurieva Marina Yurieva, Ph.D. |
Farmington, CT |
Applications in Computational Immunology and Cancer, understanding RNA Biology and splicing using multi-omics data.
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I have a diverse expertise in analysis of Multi-omics datasets, Immunology, Microbiome, Developmental Biology, RNA Biology and Cloud Computing. During my Ph.D. I studied the downstream targets of Hox genes in developing hindbrain using mouse, zebrafish and chick models. My postdoc was focused on developing Bioinformatics pipelines for the analysis of microbiome data and various immunological studies. At Jax I’ve been working with Adam Williams on identification of lncRNAs in RNA-seq and other omics datasets; with Olga Anczukow on developing pipelines for splicing analysis; and with Karolina Palucka on studies in Immunology and Covid-19 research.
Marina Yurieva on ORCID
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Bioinformatics|Cancer|Computational Biology|Immune Disorders |
Bioinformatics|Cancer|Computational Biology|Immune Disorders |
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Lab Staff |
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Zhang Ji-Gang Zhang, Ph.D. |
Bar Harbor, ME |
My interest mainly lies in developing and applying statistical, system computational approaches and machine learning algorithms to discover complex disease mechanisms, biomarkers and treatment targets by integrating multiple “omics” data.
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My research mainly focuses on genetic dissection of complex diseases using/developing the state-of-the-art multi- and inter-disciplinary approaches of genomic technologies, and statistical and bioinformatical methods. The approaches involve genome-wide association analyses, genome-wide transcriptome analyses, proteome-wide protein expression profiling, epigenetic profiling by various statistical methods, including e.g. data imputation, regularized regression, pathway analysis, fine mapping. I am interested in developing and applying statistical methods and bioinformatics tools for integrating large, complex multi-omics datasets (e.g. DNA-Seq, bulk RNA-Seq, sc/snRNA-Seq) in research, e.g. Alzheimer's disease and cancer.
Download Resume
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Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
Bioinformatics|Complex Traits|Computational Biology|Genetics and Genomics |
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Zhao Yue Zhao |
Farmington, CT |
Solving computational biology and bioinformatics problems with machine learning and statistical methods.
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The goal of my ongoing and future research is to apply machine learning and statistical methods to computational biology problems. My research emphasizes building a bridge between machine learning and statistical modeling especially deep learning and human health problem solutions.
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Bioinformatics|Computational Biology|Cancer |
Bioinformatics|Computational Biology|Cancer |
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Computational Scientist |
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Zuo Wulin Zuo, Ph.D. |
Farmington, CT |
Single-cell biology
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Computational Biology |
Computational Biology |
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