NIGMS-Supported Researchers Use Diverse Data to Understand Function of Cells in Organs

Network-wide association study (NetWAS) computational pipeline.
Network-wide association study (NetWAS) computational pipeline. Credit: Olga Troyanskaya
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The study of how cells form together in clusters and ultimately function in the context of organs is complex, difficult and incomplete. NIGMS-supported researcher Olga Troyanskaya Link to external Web site of Princeton University is using computational methods to address this gap in understanding.

Troyanskaya and her colleagues have developed methods that use complex and diverse datasets, such as gene expression data from diseased and normal tissues, information about protein interactions and regulatory information encoded in genomic sequences.

This strategy goes beyond current approaches, such as genome-wide association studies (GWAS) that find genetic variations associated with particular diseases. Troyanskaya’s system, which she calls NetWAS Link to external Web site, uses statistical and machine learning methods to combine GWAS, molecular, textual and ontological data in a mathematically consistent manner. She also combines the results with human-curated hierarchical information known as ontologies. Ontologies typically describe relationships between concepts that humans specify. For example, the Gene Ontology describes genes and their products, and the BRaunschweig ENzyme Database (BRENDA) tissue ontology describes knowledge about the relationships between organ systems.

Troyanskaya’s main scientific advance is showing that it is possible to obtain information about the context-specific behavior of cells using informatics or computational methods. This is important because scientists rarely have the resources, or even the methods, to carry out specific experiments to study every combination of cells and tissues.

Ultimately, Troyanskaya’s tool could be used for a wide variety of purposes, such as the study of basic cellular and tissue processes or tissue-specific disease analysis.

This work was partly supported with funding to Troyanskaya through grant R01GM71966.

Greene CS, Krishnan A, Wong AK, Ricciotti E, Zelaya RA, Himmelstein DS, Zhang R, Hartmann BM, Zaslavsky E, Sealfon SC, Chasman DI, FitzGerald GA, Dolinski K, Grosser T, Troyanskaya OG. Understanding multicellular function and disease with human tissue-specific networks. Nature Genetics. 2015 Apr 27;47, 569-76. PMID: 25915600.

Simons Foundation News Feature: Olga Troyanskaya Brings Order to Big Data of Human Biology Link to external Web site

For additional information, contact Peter Lyster.