Genome-scale analysis of interaction dynamics reveals organization of biological networks

被引:49
作者
Das, Jishnu [1 ,2 ]
Mohammed, Jaaved [1 ]
Yu, Haiyuan [1 ,2 ]
机构
[1] Cornell Univ, Dept Biol Stat & Computat Biol, Ithaca, NY 14853 USA
[2] Cornell Univ, Weill Inst Cell & Mol Biol, Ithaca, NY 14853 USA
关键词
PROTEIN-PROTEIN INTERACTIONS; SACCHAROMYCES-CEREVISIAE; EXPRESSION DATA; DATA SETS; TRANSPORT; SEC24P; EXPLORATION; TOOL;
D O I
10.1093/bioinformatics/bts283
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Analyzing large-scale interaction networks has generated numerous insights in systems biology. However, such studies have primarily been focused on highly co-expressed, stable interactions. Most transient interactions that carry out equally important functions, especially in signal transduction pathways, are yet to be elucidated and are often wrongly discarded as false positives. Here, we revisit a previously described Smith-Waterman-like dynamic programming algorithm and use it to distinguish stable and transient interactions on a genomic scale in human and yeast. We find that in biological networks, transient interactions are key links topologically connecting tightly regulated functional modules formed by stable interactions and are essential to maintaining the integrity of cellular networks. We also perform a systematic analysis of interaction dynamics across different technologies and find that high-throughput yeast two-hybrid is the only available technology for detecting transient interactions on a large scale.
引用
收藏
页码:1873 / 1878
页数:6
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