A proteome-scale map of the human interactome network.
A proteome-scale map of the human interactome network.
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DOI：
10.1016/j.cell.2014.10.050
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发表时间：
2014-11-20
期刊：
影响因子：
64.5
通讯作者：
Vidal M
中科院分区：
文献类型：
--
作者：
Rolland T;Taşan M;Charloteaux B;Pevzner SJ;Zhong Q;Sahni N;Yi S;Lemmens I;Fontanillo C;Mosca R;Kamburov A;Ghiassian SD;Yang X;Ghamsari L;Balcha D;Begg BE;Braun P;Brehme M;Broly MP;Carvunis AR;Convery-Zupan D;Corominas R;Coulombe-Huntington J;Dann E;Dreze M;Dricot A;Fan C;Franzosa E;Gebreab F;Gutierrez BJ;Hardy MF;Jin M;Kang S;Kiros R;Lin GN;Luck K;MacWilliams A;Menche J;Murray RR;Palagi A;Poulin MM;Rambout X;Rasla J;Reichert P;Romero V;Ruyssinck E;Sahalie JM;Scholz A;Shah AA;Sharma A;Shen Y;Spirohn K;Tam S;Tejeda AO;Wanamaker SA;Twizere JC;Vega K;Walsh J;Cusick ME;Xia Y;Barabási AL;Iakoucheva LM;Aloy P;De Las Rivas J;Tavernier J;Calderwood MA;Hill DE;Hao T;Roth FP;Vidal M
就像参考基因组序列彻底改变了人类遗传学一样，相互作用组网络的参考图谱对于充分理解基因型-表型关系至关重要。在这里，我们描述了~ 14，000个高质量人类二元蛋白质-蛋白质相互作用的系统图。在同等质量下，这张地图比过去几十年文献中发表的小规模研究大30%。虽然目前可用的信息是高度偏颇的，只涵盖了相对较小的一部分蛋白质组，我们的系统地图似乎更显着同质，揭示了一个“更广泛的”人类相互作用网络比目前所认识的。该图谱还揭示了已知和候选癌症基因产物之间的重要相互联系，为扩展的功能性癌症景观提供了无偏见的证据，同时展示了高质量的相互作用组模型将如何帮助“连接点”的基因组革命。
Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution.
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影响因子：
64.8
作者：
Kim, Min-Sik;Pinto, Sneha M.;Getnet, Derese;Nirujogi, Raja Sekhar;Manda, Srikanth S.;Chaerkady, Raghothama;Madugundu, Anil K.;Kelkar, Dhanashree S.;Isserlin, Ruth;Jain, Shobhit;Thomas, Joji K.;Muthusamy, Babylakshmi;Leal-Rojas, Pamela;Kumar, Praveen;Sahasrabuddhe, Nandini A.;Balakrishnan, Lavanya;Advani, Jayshree;George, Bijesh;Renuse, Santosh;Selvan, Lakshmi Dhevi N.;Patil, Arun H.;Nanjappa, Vishalakshi;Radhakrishnan, Aneesha;Prasad, Samarjeet;Subbannayya, Tejaswini;Raju, Rajesh;Kumar, Manish;Sreenivasamurthy, Sreelakshmi K.;Marimuthu, Arivusudar;Sathe, Gajanan J.;Chavan, Sandip;Datta, Keshava K.;Subbannayya, Yashwanth;Sahu, Apeksha;Yelamanchi, Soujanya D.;Jayaram, Savita;Rajagopalan, Pavithra;Sharma, Jyoti;Murthy, Krishna R.;Syed, Nazia;Goel, Renu;Khan, Aafaque A.;Ahmad, Sartaj;Dey, Gourav;Mudgal, Keshav;Chatterjee, Aditi;Huang, Tai-Chung;Zhong, Jun;Wu, Xinyan;Shaw, Patrick G.;Freed, Donald;Zahari, Muhammad S.;Mukherjee, Kanchan K.;Shankar, Subramanian;Mahadevan, Anita;Lam, Henry;Mitchell, Christopher J.;Shankar, Susarla Krishna;Satishchandra, Parthasarathy;Schroeder, John T.;Sirdeshmukh, Ravi;Maitra, Anirban;Leach, Steven D.;Drake, Charles G.;Halushka, Marc K.;Prasad, T. S. Keshava;Hruban, Ralph H.;Kerr, Candace L.;Bader, Gary D.;Iacobuzio-Donahue, Christine A.;Gowda, Harsha;Pandey, Akhilesh
通讯作者：
Pandey, Akhilesh
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
14.9
作者：
Chatr-Aryamontri A;Breitkreutz BJ;Heinicke S;Boucher L;Winter A;Stark C;Nixon J;Ramage L;Kolas N;O'Donnell L;Reguly T;Breitkreutz A;Sellam A;Chen D;Chang C;Rust J;Livstone M;Oughtred R;Dolinski K;Tyers M
通讯作者：
Tyers M
DOI：
10.1038/nrc1299
发表时间：
2004-03
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
通讯作者：
--
影响因子：
5.3
作者：
Nakashima, Ayumu;Kawamoto, Takeshi;Kato, Yukio
通讯作者：
Kato, Yukio