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For large libraries of small molecules, exhaustive combinatorial chemical screens become infeasible to perform when considering a range of disease models, assay conditions, and dose ranges.
Harry L Morgan · 1965
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Functional genomic hypothesis generation and experimentation by a robot scientist
Ross D. King, Kenneth E. Whelan, Ffion M. Jones, Philip G. K. Reiser, Christopher H. Bryant, Stephen H. Muggleton, Douglas B. Kell, and Stephen G. Oliver · 2004
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Novantrone: mitoxantrone for injection concentrate, additional safety information, apr 2005
EMD Serono · 2005
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Combinatorial drug therapy for cancer in the post-genomic era
Bissan Al-Lazikani, Udai Banerji, and Paul Workman · 2012
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Flumatinib, a selective inhibitor of bcr-abl/pdgfr/kit, effectively overcomes drug resistance of certain kit mutants
Jie Zhao, Haitian Quan, Yongping Xu, Xiangqian Kong, Lu Jin, and Liguang Lou · 2014
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Molecular fingerprint similarity search in virtual screening
Adrià Cereto-Massagué, María José Ojeda, Cristina Valls, Miquel Mulero, Santiago Garcia-Vallvé, and Gerard Pujadas · 2015
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Prediction of synergism from chemical-genetic interactions by machine learning
Jan Wildenhain, Michaela Spitzer, Sonam Dolma, Nick Jarvik, Rachel White, Marcia Roy, Emma Griffiths, David S Bellows, Gerard D Wright, and Mike Tyers · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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In vitro discovery of promising anti-cancer drug combinations using iterative maximisation of a therapeutic index
M. Kashif, C. Andersson, S. Hassan, H. Karlsson, W. Senkowski, M. Fryknäs, P. Nygren, R. Larsson, and M.G. Gustafsson · 2015
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ChEMBL web services: streamlining access to drug discovery data and utilities
Mark Davies, Michał Nowotka, George Papadatos, Nathan Dedman, Anna Gaulton, Francis Atkinson, Louisa Bellis, and John P Overington · 2015
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Modelling of compound combination effects and applications to efficacy and toxicity: State-of-the-art, challenges and perspectives
Krishna C. Bulusu, Rajarshi Guha, Daniel J. Mason, Richard P. I. Lewis, Eugene Muratov, Yasaman Kalantar Motamedi, Murat Cokol, and Andreas Bender · 2016
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An unbiased oncology compound screen to identify novel combination strategies
Jennifer O’Neil, Yair Benita, Igor Feldman, Melissa Chenard, Brian Roberts, Yaping Liu, Jing Li, Astrid Kral, Serguei Lejnine, Andrey Loboda, et al · 2016
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Cell painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
Mark-Anthony Bray, Shantanu Singh, Han Han, Chadwick T Davis, Blake Borgeson, Cathy Hartland, Maria Kost-Alimova, Sigrun M Gustafsdottir, Christopher C Gibson, and Anne E Carpenter · 2016
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Combination therapy in combating cancer
Reza Bayat Mokhtari, Tina S Homayouni, Narges Baluch, Evgeniya Morgatskaya, Sushil Kumar, Bikul Das, and Herman Yeger · 2017
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A review of active learning approaches to experimental design for uncovering biological networks
Yuriy Sverchkov and Mark Craven · 2017
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The National Cancer Institute ALMANAC: a comprehensive screening resource for the detection of anticancer drug pairs with enhanced therapeutic activity
Susan L Holbeck, Richard Camalier, James A Crowell, Jeevan Prasaad Govindharajulu, Melinda Hollingshead, Lawrence W Anderson, Eric Polley, Larry Rubinstein, Apurva Srivastava, Deborah Wilsker, et al · 2017
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A next generation connectivity map: L1000 platform and the first 1,000,000 profiles
Aravind Subramanian, Rajiv Narayan, Steven M Corsello, David D Peck, Ted E Natoli, Xiaodong Lu, Joshua Gould, John F Davis, Andrew A Tubelli, Jacob K Asiedu, et al · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles, 2017
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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The reframe library as a comprehensive drug repurposing library and its application to the treatment of cryptosporidiosis
Jeff Janes, Megan E Young, Emily Chen, Nicole H Rogers, Sebastian Burgstaller-Muehlbacher, Laura D Hughes, Melissa S Love, Mitchell V Hull, Kelli L Kuhen, Ashley K Woods, et al · 2018
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Integrative omics for health and disease
Konrad J Karczewski and Michael P Snyder · 2018
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Modeling polypharmacy side effects with graph convolutional networks
Marinka Zitnik, Monica Agrawal, and Jure Leskovec · 2018
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Copy number variation is highly correlated with differential gene expression: a pan-cancer study
Xin Shao, Ning Lv, Jie Liao, Jinbo Long, Rui Xue, Ni Ai, Donghang Xu, and Xiaohui Fan · 2019
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Identifying significantly impacted pathways: a comprehensive review and assessment
Tuan-Minh Nguyen, Adib Shafi, Tin Nguyen, and Sorin Draghici · 2019
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Simulated ablation for detection of cells impacting paracrine signalling in histology analysis
Jake P Taylor-King, Etienne Baratchart, Andrew Dhawan, Elizabeth A Coker, Inga Hansine Rye, Hege Russnes, S Jon Chapman, David Basanta, and Andriy Marusyk · 2019
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Pubchem 2019 update: improved access to chemical data
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Artificial intelligence in covid-19 drug repurposing
Yadi Zhou, Fei Wang, Jian Tang, Ruth Nussinov, and Feixiong Cheng · 2020
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Deepsynergy: predicting anti-cancer drug synergy with deep learning
Kristina Preuer, Richard PI Lewis, Sepp Hochreiter, Andreas Bender, Krishna C Bulusu, and Günter Klambauer · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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An automated design-build-test-learn pipeline for enhanced microbial production of fine chemicals
Pablo Carbonell, Adrian J. Jervis, Christopher J. Robinson, Cunyu Yan, Mark Dunstan, Neil Swainston, Maria Vinaixa, Katherine A. Hollywood, Andrew Currin, Nicholas J. W. Rattray, Sandra Taylor, Reynard Spiess, Rehana Sung, Alan R. Williams, Donal Fellows, Natalie J. Stanford, Paul Mulherin, Rosalind Le Feuvre, Perdita Barran, Royston Goodacre, Nicholas J. Turner, Carole Goble, George Guoqiang Chen, Douglas B. Kell, Jason Micklefield, Rainer Breitling, Eriko Takano, Jean-Loup Faulon, and Nigel S. Scrutton · 2018
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Drug combinations: a strategy to extend the life of antibiotics in the 21st century
Mike Tyers and Gerard D Wright · 2019
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Highlights in resistance mechanism pathways for combination therapy
João Delou, Alana SO Souza, Leonel Souza, and Helena L Borges · 2019
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Industrial scale high-throughput screening delivers multiple fast acting macrofilaricides
Rachel H Clare, Catherine Bardelle, Paul Harper, W David Hong, Ulf Börjesson, Kelly L Johnston, Matthew Collier, Laura Myhill, Andrew Cassidy, Darren Plant, et al · 2019
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Network-based prediction of drug combinations
Feixiong Cheng, István A Kovács, and Albert-László Barabási · 2019
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Advances in exploring activity cliffs
Dagmar Stumpfe, Huabin Hu, and Jürgen Bajorath · 2020
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Large scale active-learning-guided exploration for in vitro protein production optimization
Olivier Borkowski, Mathilde Koch, Agnès Zettor, Amir Pandi, Angelo Cardoso Batista, Paul Soudier, and Jean-Loup Faulon · 2020
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Leveraging uncertainty in machine learning accelerates biological discovery and design
Brian Hie, Bryan D Bryson, and Bonnie Berger · 2020
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Deep learning identifies synergistic drug combinations for treating covid-19
Wengong Jin, Jonathan M Stokes, Richard T Eastman, Zina Itkin, Alexey V Zakharov, James J Collins, Tommi S Jaakkola, and Regina Barzilay · 2021
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Moomin: Deep molecular omics network for anti-cancer drug combination therapy
Benedek Rozemberczki, Anna Gogleva, Sebastian Nilsson, Gavin Edwards, Andriy Nikolov, and Eliseo Papa · 2021
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Combination strategies to maximize the benefits of cancer immunotherapy
Shaoming Zhu, Tian Zhang, Lei Zheng, Hongtao Liu, Wenru Song, Delong Liu, Zihai Li, and Chong-xian Pan · 2021
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Effective gene expression prediction from sequence by integrating long-range interactions
Ziga Avsec, Vikram Agarwal, Daniel Visentin, Joseph R Ledsam, Agnieszka Grabska-Barwinska, Kyle R Taylor, Yannis Assael, John Jumper, Pushmeet Kohli, and David R Kelley · 2021
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Rethinking rare disease: longevity-enhancing drug targets through x-linked aneuploidy
Jake P Taylor-King · 2021
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Utilizing graph machine learning within drug discovery and development
Thomas Gaudelet, Ben Day, Arian R Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy BR Hayter, Richard Vickers, Charles Roberts, Jian Tang, et al · 2021
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High-throughput microwell-seq 2.0 profiles massively multiplexed chemical perturbation
Haide Chen, Yuan Liao, Guodong Zhang, Zhongyi Sun, Lei Yang, Xing Fang, Huiyu Sun, Lifeng Ma, Yuting Fu, Jingyu Li, et al · 2021
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DEUP: direct epistemic uncertainty prediction
Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, and Yoshua Bengio · 2021
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scperturb: Information resource for harmonized single-cell perturbation data
Stefan Peidli, Tessa Durakis Green, Ciyue Shen, Torsten Gross, Joseph Min, Jake Taylor-King, Debora Marks, Augustin Luna, Nils Bluthgen, and Chris Sander · 2022
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Effective drug combinations in breast, colon and pancreatic cancer cells
Patricia Jaaks, Elizabeth A Coker, Daniel J Vis, Olivia Edwards, Emma F Carpenter, Simonetta M Leto, Lisa Dwane, Francesco Sassi, Howard Lightfoot, Syd Barthorpe, et al · 2022
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