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Workshop Content

This workshop introduces a variety of pathway informatics tools. First we will learn how to mine a list of differentially expressed genes associated with a disease of interest by searching the Gene Expression Omnibus (GEO) using NextBio and GEO2R. Then we will focus on uncovering the biology hidden behind the extracted gene list by searching protein-protein interaction and literature curated gene/protein knowledge bases using pathway informatics software, including  Ingenuity IPA, Metacore, Reactome and NIH DAVID . 



1.   Szklarczyk, D. et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43, D447–D452 (2015).

2.   Barrett, T. et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 41, D991–D995 (2013).

3.   Kolesnikov, N. et al. ArrayExpress update--simplifying data submissions. Nucleic Acids Res 43, D1113–D1116 (2015).

4.   Whyte, L., Huang, Y. Y., Torres, K. & Mehta, R. G. Molecular mechanisms of resveratrol action in lung cancer cells using dual protein and microarray analyses. Cancer Res 67, 12007–12017 (2007).

5.   Kupershmidt, I. et al. Ontology-based meta-analysis of global collections of high-throughput public data. PLoS ONE 5, (2010).

6.   Huang, D. A. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4, 44–57 (2009).

7.   Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).

8.   Gundersen, G. W. et al. GEO2Enrichr: browser extension and server app to extract gene sets from GEO and analyze them for biological functions. Bioinformatics 31, 3060–3062 (2015).

9.   Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102, 15545–15550 (2005).

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