Principles for the organization of gene-sets. (December 2015)

• Record Type: Journal Article
• Authors: Li, Wentian; Freudenberg, Jan; Oswald, Michaela
• Is Part Of: Computational biology and chemistry. Volume 59:Part B(2015)
• Page Start: 139
• Page End: 149
• Publication Date: 2015-12
• Subjects: Gene-sets -- Gene families -- Co-localization -- Operon -- Protein complex -- Protein domains -- Protein–protein interaction -- Transcription factor target -- Gene Ontology (GO) -- Biological pathways -- Co-expression -- Co-differential expression -- Essential genes -- Housekeeping genes -- Tissue-specific genes -- Disease genes -- Modules; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2015.04.005
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs.