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Predicted yeast interactome and network‐based interpretation of transcriptionally changed genes
Author(s) -
Jin Jie,
Tao YuTian,
Ding XiaoBao,
Guo WenPing,
Ruan Li,
Yang Qiaolei,
Chen PengCheng,
Yao Heng,
Zhang Haibo,
Chen Xin
Publication year - 2020
Publication title -
yeast
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.923
H-Index - 102
eISSN - 1097-0061
pISSN - 0749-503X
DOI - 10.1002/yea.3516
Subject(s) - interactome , biology , gene , computational biology , saccharomyces cerevisiae , yeast , model organism , genetics , gene regulatory network , gene nomenclature , annotation , budding yeast , set (abstract data type) , organism , gene expression , computer science , nomenclature , programming language , botany , taxonomy (biology)
Saccharomyces cerevisiae, budding yeast, is a widely used model organism and research tool in genetics studies. Many efforts have been directed at constructing a high-quality comprehensive molecular interaction network to elucidate the design logic of the gene circuitries in this classic model organism. In this work, we present the yeast interactome resource (YIR), which includes 22,238 putative functional gene interactions inferred from functional gene association data integrated from 10 databases focusing on diverse functional perspectives. These putative functional gene interactions are expected to cover 18.84% of yeast protein interactions, and 38.49% may represent protein interactions. Based on the YIR, a gene set linkage analysis (GSLA) web tool was developed to annotate the potential functional impacts of a set of transcriptionally changed genes. In a case study, we show that the YIR/GSLA system produced more extensive and concise annotations compared with widely used gene set annotation tools, including PANTHER and DAVID. Both YIR and GSLA are accessible through the website http://yeast.biomedtzc.cn.