Venkatesan Kavitha, Rual Jean-François, Vazquez Alexei, Stelzl Ulrich, Lemmens Irma, Hirozane-Kishikawa Tomoko, Hao Tong, Zenkner Martina, Xin Xiaofeng, Goh Kwang-Il, Yildirim Muhammed A, Simonis Nicolas, Heinzmann Kathrin, Gebreab Fana, Sahalie Julie M, Cevik Sebiha, Simon Christophe, de Smet Anne-Sophie, Dann Elizabeth, Smolyar Alex, Vinayagam Arunachalam, Yu Haiyuan, Szeto David, Borick Heather, Dricot Amélie, Klitgord Niels, Murray Ryan R, Lin Chenwei, Lalowski Maciej, Timm Jan, Rau Kirstin, Boone Charles, Braun Pascal, Cusick Michael E, Roth Frederick P, Hill David E, Tavernier Jan, Wanker Erich E, Barabási Albert-László, Vidal Marc
Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, 1 Jimmy Fund Way, Boston, MA 02115, USA.
Nat Methods. 2009 Jan;6(1):83-90. doi: 10.1038/nmeth.1280. Epub 2008 Dec 7.
Several attempts have been made to systematically map protein-protein interaction, or 'interactome', networks. However, it remains difficult to assess the quality and coverage of existing data sets. Here we describe a framework that uses an empirically-based approach to rigorously dissect quality parameters of currently available human interactome maps. Our results indicate that high-throughput yeast two-hybrid (HT-Y2H) interactions for human proteins are more precise than literature-curated interactions supported by a single publication, suggesting that HT-Y2H is suitable to map a significant portion of the human interactome. We estimate that the human interactome contains approximately 130,000 binary interactions, most of which remain to be mapped. Similar to estimates of DNA sequence data quality and genome size early in the Human Genome Project, estimates of protein interaction data quality and interactome size are crucial to establish the magnitude of the task of comprehensive human interactome mapping and to elucidate a path toward this goal.
人们已经进行了多次尝试,以系统地绘制蛋白质-蛋白质相互作用网络,即“相互作用组”网络。然而,评估现有数据集的质量和覆盖范围仍然很困难。在这里,我们描述了一个框架,该框架使用基于经验的方法来严格剖析当前可用的人类相互作用组图谱的质量参数。我们的结果表明,人类蛋白质的高通量酵母双杂交(HT-Y2H)相互作用比单一出版物支持的文献整理相互作用更精确,这表明HT-Y2H适合绘制人类相互作用组的很大一部分。我们估计人类相互作用组包含大约130,000个二元相互作用,其中大部分仍有待绘制。类似于人类基因组计划早期对DNA序列数据质量和基因组大小的估计,蛋白质相互作用数据质量和相互作用组大小的估计对于确定全面绘制人类相互作用组任务的规模以及阐明实现这一目标的途径至关重要。