A community computational challenge to predict the activity of pairs of compounds.
A community computational challenge to predict the activity of pairs of compounds.
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DOI：
10.1038/nbt.3052
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发表时间：
2014-12
影响因子：
46.9
通讯作者：
Zhou, Jian
中科院分区：
文献类型：
--
作者：
Bansal, Mukesh;Yang, Jichen;Karan, Charles;Menden, Michael P.;Costello, James C.;Tang, Hao;Xiao, Guanghua;Li, Yajuan;Allen, Jeffrey;Zhong, Rui;Chen, Beibei;Kim, Minsoo;Wang, Tao;Heiser, Laura M.;Realubit, Ronald;Mattioli, Michela;Alvarez, Mariano J.;Shen, Yao;Gallahan, Daniel;Singer, Dinah;Saez-Rodriguez, Julio;Xie, Yang;Stolovitzky, Gustavo;Califano, Andrea;Abbuehl, Jean-Paul;Altman, Russ B.;Balcome, Shawn;Bell, Ana;Bender, Andreas;Berger, Bonnie;Bernard, Jonathan;Bieberich, Andrew A.;Borboudakis, Giorgos;Chan, Christina;Chen, Ting-Huei;Choi, Jaejoon;Coelho, Luis Pedro;Creighton, Chad J.;Dampier, Will;Davisson, V. Jo;Deshpande, Raamesh;Diao, Lixia;Di Camillo, Barbara;Dundar, Murat;Ertel, Adam;Goswami, Chirayu P.;Gottlieb, Assaf;Gould, Michael N.;Goya, Jonathan;Grau, Michael;Gray, Joe W.;Hejase, Hussein A.;Hoffmann, Michael F.;Homicsko, Krisztian;Homilius, Max;Hwang, Woochang;Ijzerman, Adriaan P.;Kallioniemi, Olli;Karacali, Bilge;Kaski, Samuel;Kim, Junho;Krishnan, Arjun;Lee, Junehawk;Lee, Young-Suk;Lenselink, Eelke B.;Lenz, Peter;Li, Lang;Li, Jun;Liang, Han;Mpindi, John-Patrick;Myers, Chad L.;Newton, Michael A.;Overington, John P.;Parkkinen, Juuso;Prill, Robert J.;Peng, Jian;Pestell, Richard;Qiu, Peng;Rajwa, Bartek;Sadanandam, Anguraj;Sambo, Francesco;Sridhar, Arvind;Sun, Wei;Toffolo, Gianna M.;Tozeren, Aydin;Troyanskaya, Olga G.;Tsamardinos, Ioannis;van Vlijmen, Herman W. T.;Wang, Wen;Wegner, Joerg K.;Wennerberg, Krister;van Westen, Gerard J. P.;Xia, Tian;Yang, Yang;Yao, Victoria;Yuan, Yuan;Zeng, Haoyang;Zhang, Shihua;Zhao, Junfei;Zhou, Jian
最近的治疗成功重新引起了人们对药物组合的兴趣，但实验筛选方法成本高昂，并且通常只能识别少量的协同组合。DREAM联盟发起了一项公开挑战，以促进计算机模拟方法的发展，根据在多个时间点和浓度下用单个化合物处理的人类B细胞的基因表达谱，对91种化合物对进行计算排名，从最具协同作用到最具拮抗作用。使用基于实验剂量反应曲线的评分指标，我们评估了32种方法（31种社区生成的方法和SynGen），其中4种方法的表现明显优于随机猜测。我们强调方法之间的相似之处。虽然预测的准确性不是最佳的，但我们发现化合物对活性的计算预测是可能的，并且社区挑战可以用于推进计算机化合物协同预测领域。
Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.
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影响因子：
20.3
作者：
Green, Michael R.;Monti, Stefano;Shipp, Margaret A.
通讯作者：
Shipp, Margaret A.
影响因子：
9.9
作者：
Lefebvre, Celine;Rajbhandari, Presha;Alvarez, Mariano J.;Bandaru, Pradeep;Lim, Wei Keat;Sato, Mai;Wang, Kai;Sumazin, Pavel;Kustagi, Manjunath;Bisikirska, Brygida C.;Basso, Katia;Beltrao, Pedro;Krogan, Nevan;Gautier, Jean;Dalla-Favera, Riccardo;Califano, Andrea
通讯作者：
Califano, Andrea
影响因子：
48
作者：
Marbach, Daniel;Costello, James C.;Kueffner, Robert;Vega, Nicole M.;Prill, Robert J.;Camacho, Diogo M.;Allison, Kyle R.;Kellis, Manolis;Collins, James J.;Stolovitzky, Gustavo
通讯作者：
Stolovitzky, Gustavo
影响因子：
46.9
作者：
Lehar, Joseph;Krueger, Andrew S.;Avery, William;Heilbut, Adrian M.;Johansen, Lisa M.;Price, E. Roydon;Rickles, Richard J.;Short, Glenn F., III;Staunton, Jane E.;Jin, Xiaowei;Lee, Margaret S.;Zimmermann, Grant R.;Borisy, Alexis A.
通讯作者：
Borisy, Alexis A.
影响因子：
1.6
作者：
Araujo, RP;Petricoin, EF;Liotta, LA
通讯作者：
Liotta, LA