Literature DB >> 21587249

An active role for machine learning in drug development.

Robert F Murphy1.   

Abstract

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Year:  2011        PMID： 21587249      PMCID： PMC4107394          DOI： 10.1038/nchembio.576

Source DB:  PubMed          Journal:  Nat Chem Biol        ISSN： 1552-4450            Impact factor:   15.040


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  19 in total

1.  Active learning with support vector machines in the drug discovery process.

Authors:  Manfred K Warmuth; Jun Liao; Gunnar Rätsch; Michael Mathieson; Santosh Putta; Christian Lemmen
Journal:  J Chem Inf Comput Sci       Date:  2003 Mar-Apr

2.  Past, present, and future of high content screening and the field of cellomics.

Authors:  D Lansing Taylor
Journal:  Methods Mol Biol       Date:  2007

3.  Choosing where to look next in a mutation sequence space: Active Learning of informative p53 cancer rescue mutants.

Authors:  Samuel A Danziger; Jue Zeng; Ying Wang; Rainer K Brachmann; Richard H Lathrop
Journal:  Bioinformatics       Date:  2007-07-01       Impact factor: 6.937

4.  Cellular systems biology profiling applied to cellular models of disease.

Authors:  Kenneth A Giuliano; Daniel R Premkumar; Christopher J Strock; Patricia Johnston; Lansing Taylor
Journal:  Comb Chem High Throughput Screen       Date:  2009-11       Impact factor: 1.339

5.  Image-derived, three-dimensional generative models of cellular organization.

Authors:  Tao Peng; Robert F Murphy
Journal:  Cytometry A       Date:  2011-04-06       Impact factor: 4.355

Review 6.  Impact of high-throughput screening in biomedical research.

Authors:  Ricardo Macarron; Martyn N Banks; Dejan Bojanic; David J Burns; Dragan A Cirovic; Tina Garyantes; Darren V S Green; Robert P Hertzberg; William P Janzen; Jeff W Paslay; Ulrich Schopfer; G Sitta Sittampalam
Journal:  Nat Rev Drug Discov       Date:  2011-03       Impact factor: 84.694

7.  Active learning for human protein-protein interaction prediction.

Authors:  Thahir P Mohamed; Jaime G Carbonell; Madhavi K Ganapathiraju
Journal:  BMC Bioinformatics       Date:  2010-01-18       Impact factor: 3.169

8.  Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.

Authors:  Samuel A Danziger; Roberta Baronio; Lydia Ho; Linda Hall; Kirsty Salmon; G Wesley Hatfield; Peter Kaiser; Richard H Lathrop
Journal:  PLoS Comput Biol       Date:  2008-09-04       Impact factor: 4.475

9.  Predicting and understanding the stability of G-quadruplexes.

Authors:  Oliver Stegle; Linda Payet; Jean-Louis Mergny; David J C MacKay; Julian Huppert Leon
Journal:  Bioinformatics       Date:  2009-06-15       Impact factor: 6.937

10.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes.

Authors:  Anne E Carpenter; Thouis R Jones; Michael R Lamprecht; Colin Clarke; In Han Kang; Ola Friman; David A Guertin; Joo Han Chang; Robert A Lindquist; Jason Moffat; Polina Golland; David M Sabatini
Journal:  Genome Biol       Date:  2006-10-31       Impact factor: 13.583
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  23 in total

1.  Integrated 3D-printed reactionware for chemical synthesis and analysis.

Authors:  Mark D Symes; Philip J Kitson; Jun Yan; Craig J Richmond; Geoffrey J T Cooper; Richard W Bowman; Turlif Vilbrandt; Leroy Cronin
Journal:  Nat Chem       Date:  2012-04-15       Impact factor: 24.427

2.  CellOrganizer: Image-derived models of subcellular organization and protein distribution.

Authors:  Robert F Murphy
Journal:  Methods Cell Biol       Date:  2012       Impact factor: 1.441

3.  A multiparametric organ toxicity predictor for drug discovery.

Authors:  Chirag N Patel; Sivakumar Prasanth Kumar; Rakesh M Rawal; Daxesh P Patel; Frank J Gonzalez; Himanshu A Pandya
Journal:  Toxicol Mech Methods       Date:  2019-10-29       Impact factor: 2.987

4.  Biological imaging software tools.

Authors:  Kevin W Eliceiri; Michael R Berthold; Ilya G Goldberg; Luis Ibáñez; B S Manjunath; Maryann E Martone; Robert F Murphy; Hanchuan Peng; Anne L Plant; Badrinath Roysam; Nico Stuurman; Nico Stuurmann; Jason R Swedlow; Pavel Tomancak; Anne E Carpenter
Journal:  Nat Methods       Date:  2012-06-28       Impact factor: 28.547

5.  Efficient modeling and active learning discovery of biological responses.

Authors:  Armaghan W Naik; Joshua D Kangas; Christopher J Langmead; Robert F Murphy
Journal:  PLoS One       Date:  2013-12-17       Impact factor: 3.240

6.  Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Authors:  See Hong Chiu; Lei Xie
Journal:  J Chem Inf Model       Date:  2016-05-20       Impact factor: 4.956

Review 7.  Image analysis in fluorescence microscopy: bacterial dynamics as a case study.

Authors:  Sven van Teeffelen; Joshua W Shaevitz; Zemer Gitai
Journal:  Bioessays       Date:  2012-03-13       Impact factor: 4.345

8.  Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification.

Authors:  Lokmane Chebouba; Dalila Boughaci; Carito Guziolowski
Journal:  J Med Syst       Date:  2018-06-04       Impact factor: 4.460

9.  Measuring Nanoparticle Penetration Through Bio-Mimetic Gels.

Authors:  Scott C McCormick; Namid Stillman; Matthew Hockley; Adam W Perriman; Sabine Hauert
Journal:  Int J Nanomedicine       Date:  2021-03-30

10.  A multi-label approach to target prediction taking ligand promiscuity into account.

Authors:  Hamse Y Mussa; Andreas Bender; Avid M Afzal; Richard E Turner; Robert C Glen
Journal:  J Cheminform       Date:  2015-05-30       Impact factor: 5.514
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