GeneWeaver

Gene Weaver is a powerful web-based data and analysis software system designed to find a convergent signal in noisy functional genomics data.

There are many roadblocks to a coherent integration of functional genomic data, including diverse experimental approaches, differences across species, divergent data formats, non-standardized vocabularies, imprecise or incomplete genotype-phenotype associations, and more. GeneWeaver overcomes the roadblocks by allowing researchers to readily integrate and analyze genome-wide experimental data across multiple protocols and several widely studied species.

Gene Weaver provides:

• The ability to upload experimental data sets for analysis in combination with the system’s incorporated data
• A data repository containing more than 130,500 gene sets consisting of more than 1,986,743 genomic features.
• Flexible gene search options, including field-restricted queries and Boolean search
• Powerful combinatorial and statistical analysis tools

• Data from expression microarray, RNA-seq, QTL mapping, GWAS, and mutation and perturbation screening experiments
• Biological relationship/phenotype data
• Network and pathway members
• Gene regulatory relations
• Large community data sources
• Human and model organism data in one comparative analysis platform (yeast, worm, fly, zebrafish, mouse, rat, dog, human and other species)

Gene Weaver puts biologists in the driver’s seat by providing on-demand analysis of user selected and user entered heterogeneous data, identifying convergent data signals, and yielding testable hypotheses.

Using Gene Weaver, researchers are able to compare and contrast results among a large number of related experiments, thereby classifying many biological phenomena. Noisy gene-function associations can be verified and established with more precision, and convergent evidence for novel roles of genes and associated traits can be rapidly identified from large data collections.

Gene Weaver allows users to ask questions in integrative functional genomics, such as:

• “Which genes and gene products are reliably associated with biological processes?”
• “Which candidates from genetic experiments have functional relevance?”
• “What are the common underlying molecular mechanisms of related biological processes?”
• “What are the distinct molecular substrates associated with different disease characteristics?”
• “Which animal models are most reflective of which aspects of the human disease?”

Using a flexible suite of analysis tools, biologists are able to select data and develop customized workflows to answer these and other questions. A new release of the site is completely modernized with enhanced visualization, many new features, and a fully programmable interface for reproducible analysis.

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