Coverart for item
The Resource Bioinformatics and drug discovery, edited by Richard S. Larson, Tudor I. Oprea

Bioinformatics and drug discovery, edited by Richard S. Larson, Tudor I. Oprea

Label
Bioinformatics and drug discovery
Title
Bioinformatics and drug discovery
Statement of responsibility
edited by Richard S. Larson, Tudor I. Oprea
Contributor
Editor
Subject
Genre
Language
eng
Member of
Cataloging source
RML
Dewey number
571.6
Illustrations
illustrations
Index
index present
LC call number
QH583.2
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Larson, Richard S.
  • Oprea, Tudor I.
Series statement
Methods in molecular biology,
Series volume
1939
http://library.link/vocab/subjectName
  • Cytology
  • Computational Biology
  • Drug Design
Label
Bioinformatics and drug discovery, edited by Richard S. Larson, Tudor I. Oprea
Instantiates
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Guide to dictionary-based text mining
  • Helen V. Cook and Lars Juhl Jensen
  • Leveraging big data to transform drug discovery
  • Benjamin S. Glicksberg, Li Li, Rong Chen, Joel Dudley, and Bin Chen
  • How to prepare a compound collection prior to virtual screening
  • Cristian G. Bologa, Oleg Ursu, and Tudor I. Oprea
  • Building a quantitative structure-property relationship (QSPR) model
  • Robert D. Clark and Pankaj R. Daga
  • Isomeric and conformational analysis of small drug and drug-like molecules by ion mobility-mass spectrometry (IM-MS)
  • Shawn T. Phillips, James N. Dodds, Jody C. May, and John A. McLean
  • Miniaturized checkerboard assays to measure antibiotic interactions
  • Computational platform and guide for acceleration of novel medicines and personalized medicine
  • Ioannis N. Melas, Theodore Sakellaropoulos, Junguk Hur, Dimitris Messinis, Ellen Y. Guo, Leonidas G. Alexopoulos, and Jane P. F. Bai
  • Omics data integration and analysis for systems pharmacology
  • Hansaim Lim and Lei Xie
  • Bioinformatics-based tools and software in clinical research : a new emerging area
  • Parveen Bansal, Malika Arora, Vikas Gupta, and Mukesh Maithani
  • Text mining for drug discovery
  • Si Zheng, Shazia Dharssi, Meng Wu, Jiao Li, and Zhiyong Lu
  • Big data cohort extraction for personalized statin treatment and machine learning
  • Terrence J. Adam and Chih-Lin Chi
  • Melike Cokol-Cakmak and Murat Cokol
  • Drug signature detection based on L1000 genomic and proteomic big data
  • Wei Chen and Xiaobo Zhou
  • Drug effect prediction by integrating L1000 genomic and proteomic big data
  • Wei Chen and Xiaobo Zhou
  • Bayesian network approach to disease subtype discovery
  • Mei-Sing Ong
  • High-throughput screening for drug combinations
  • Paul Shinn, Lu Chen, Marc Ferrer, Zina Itkin, Carleen Klumpp-Thomas, Crystal McKnight, Sam Michael, Tim Mierzwa, Craig Thomas, Kelli Wilson, and Rajarshi Guha
  • Post-processing of large bioactivity data
  • Jason Bret Harris
  • How to develop a drug target ontology : KNowledge Acquisition and Representation Methodology (KNARM)
  • Hande Kucuk McGinty, Ubbo Visser, and Stephan Schurer
Dimensions
unknown
Edition
Third edition
Extent
1 online resource (xi, 324 pages)
File format
unknown
Form of item
online
Isbn
9781493990887
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Label
Bioinformatics and drug discovery, edited by Richard S. Larson, Tudor I. Oprea
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Guide to dictionary-based text mining
  • Helen V. Cook and Lars Juhl Jensen
  • Leveraging big data to transform drug discovery
  • Benjamin S. Glicksberg, Li Li, Rong Chen, Joel Dudley, and Bin Chen
  • How to prepare a compound collection prior to virtual screening
  • Cristian G. Bologa, Oleg Ursu, and Tudor I. Oprea
  • Building a quantitative structure-property relationship (QSPR) model
  • Robert D. Clark and Pankaj R. Daga
  • Isomeric and conformational analysis of small drug and drug-like molecules by ion mobility-mass spectrometry (IM-MS)
  • Shawn T. Phillips, James N. Dodds, Jody C. May, and John A. McLean
  • Miniaturized checkerboard assays to measure antibiotic interactions
  • Computational platform and guide for acceleration of novel medicines and personalized medicine
  • Ioannis N. Melas, Theodore Sakellaropoulos, Junguk Hur, Dimitris Messinis, Ellen Y. Guo, Leonidas G. Alexopoulos, and Jane P. F. Bai
  • Omics data integration and analysis for systems pharmacology
  • Hansaim Lim and Lei Xie
  • Bioinformatics-based tools and software in clinical research : a new emerging area
  • Parveen Bansal, Malika Arora, Vikas Gupta, and Mukesh Maithani
  • Text mining for drug discovery
  • Si Zheng, Shazia Dharssi, Meng Wu, Jiao Li, and Zhiyong Lu
  • Big data cohort extraction for personalized statin treatment and machine learning
  • Terrence J. Adam and Chih-Lin Chi
  • Melike Cokol-Cakmak and Murat Cokol
  • Drug signature detection based on L1000 genomic and proteomic big data
  • Wei Chen and Xiaobo Zhou
  • Drug effect prediction by integrating L1000 genomic and proteomic big data
  • Wei Chen and Xiaobo Zhou
  • Bayesian network approach to disease subtype discovery
  • Mei-Sing Ong
  • High-throughput screening for drug combinations
  • Paul Shinn, Lu Chen, Marc Ferrer, Zina Itkin, Carleen Klumpp-Thomas, Crystal McKnight, Sam Michael, Tim Mierzwa, Craig Thomas, Kelli Wilson, and Rajarshi Guha
  • Post-processing of large bioactivity data
  • Jason Bret Harris
  • How to develop a drug target ontology : KNowledge Acquisition and Representation Methodology (KNARM)
  • Hande Kucuk McGinty, Ubbo Visser, and Stephan Schurer
Dimensions
unknown
Edition
Third edition
Extent
1 online resource (xi, 324 pages)
File format
unknown
Form of item
online
Isbn
9781493990887
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

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