Big data mining powers fungal research: recent advances in fission yeast systems biology approaches

被引：8
作者：
Wang, Zhe [1 ,2 ]
机构：
[1] Fudan Univ, Sch Life Sci, State Key Lab Genet Engn, 2005 Song Hu Rd, Shanghai 200438, Peoples R China
[2] Cornell Univ, Weill Med Coll, Div Infect Dis, 413 E 69th St, New York, NY 10021 USA
来源：
CURRENT GENETICS | 2017年 / 63卷 / 03期
基金：
中国国家自然科学基金; 美国国家科学基金会;
关键词：
Schizosaccharomyces pombe; Systems biology; Big data; Omics; SCHIZOSACCHAROMYCES-POMBE; TRANSCRIPTION FACTOR; FUNCTIONAL GENOMICS; CELL-CYCLE; SACCHAROMYCES; NETWORK; CONSERVATION; METABOLOMICS; RESOLUTION; DIVERSITY;
D O I：
10.1007/s00294-016-0657-4
中图分类号：
Q3 [遗传学];
学科分类号：
071007 ; 090102 ;
摘要：
Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening. We therefore hope this review can be useful for interested fungal researchers as well as bioformaticians.
引用
收藏
页码：427 / 433
页数：7
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