The goal of his group. Is to empower humans to effectively interact with data. This involves solving problems that span the areas of database systems, visualization, human-computer interaction, and information retrieval.

RNA-Enrich option for RNA-seq data. This relationship has been shown to bias gene set enrichment testing. RNA-Enrich accounts for this bias empirically. Adjusting for read counts per gene improves the type 1 error rate and power of the test. The use of logistic regression.

Tools and technology seminar series. Seminar information is now listed on the. U-M Department of Computational Medicine and Bioinformatics website. Relevant tools for analytically exploring the .

Currently, we are focusing on tools to measure the brain and body at work. Data from EEG, eye-tracking, motion capture and the environment provide a new and data-intensive glimpse of life in an event-rich world.

The NCIBI web services provide programmatic access NCIBI data. Click on the tab above for instructions for using the particular service. Protein-protein interactions, pathways, compounds, literature, and genes merged from multiple sources. To use the web interface. Enriched for a particular gene. Enriched for a particular MeSH term. To use the web interface. Enriched for a particular compound.

ChIP-Enrich tests ChIP-seq peak data for enrichment of biological pathways, Gene Ontology terms, and other types of gene sets. The pre-defined gene sets are the same as used in LRpath. And can be browsed here. ENCODE enrichment testing results can be accessed here. Number of peaks a gene must ha.