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Predicted yeast interactome and network-based interpretation of transcriptionally changed genes.
Jin, Jie; Tao, Yu-Tian; Ding, Xiao-Bao; Guo, Wen-Ping; Ruan, Li; Yang, Qiao-Lei; Chen, Peng-Cheng; Yao, Heng; Zhang, Hai-Bo; Chen, Xin.
Afiliação
  • Jin J; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Tao YT; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Ding XB; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Guo WP; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Ruan L; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Yang QL; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Chen PC; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yao H; Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
  • Zhang HB; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
  • Chen X; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, China.
Yeast ; 37(11): 573-583, 2020 11.
Article em En | MEDLINE | ID: mdl-32738156
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Transcrição Gênica / Proteínas de Saccharomyces cerevisiae Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Transcrição Gênica / Proteínas de Saccharomyces cerevisiae Idioma: En Ano de publicação: 2020 Tipo de documento: Article