title: Genome-scale analysis of interaction dynamics reveals organization of biological networks.
abstract: 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.
authors.affiliation: Department of Biological Statistics and Computational Biology, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.
authors.forename: Jishnu
authors.initials: J
authors.lastname: Das
authors.forename: Jaaved
authors.initials: J
authors.lastname: Mohammed
authors.forename: Haiyuan
authors.initials: H
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D023281:Genomics / Q000379:methods*; D006801:Humans; D012441:Saccharomyces cerevisiae / Q000235:genetics; D015398:Signal Transduction / Q000235:genetics; D049490:Systems Biology; D020798:Two-Hybrid System Techniques