Annual Reports in Computational Chemistry: Annual Reports in Computational Chemistry, cartea 4
Editat de Ralph A. Wheeler, David Spellmeyeren Limba Engleză Hardback – 30 dec 2008
- Broad coverage of computational chemistry and up-to-date information
- Topics covered include bioinformatics, drug discovery, protein NMR, simulation methodologies, and applications in academic and industrial settings
- Each chapter reviews the most recent literature on a specific topic of interest to computational chemists
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Specificații
ISBN-13: 9780444532503
ISBN-10: 0444532501
Pagini: 272
Dimensiuni: 152 x 229 x 16 mm
Greutate: 0.53 kg
Ediția:New.
Editura: ELSEVIER SCIENCE
Seria Annual Reports in Computational Chemistry
ISBN-10: 0444532501
Pagini: 272
Dimensiuni: 152 x 229 x 16 mm
Greutate: 0.53 kg
Ediția:New.
Editura: ELSEVIER SCIENCE
Seria Annual Reports in Computational Chemistry
Public țintă
Researchers and students interested in computational chemistryCuprins
Section 1: Bioinformatics (Section Editor: Wei Wang)
1. Structural Perspectives on Protein Evolution - Eric Franzosa and Yu Xia
2. Predicting Selectivity and Druggability in Drug Discovery - Alan C. Cheng
Section 2: Biological Modeling (Section Editor: Nathan Barker)
3. Machine Learning for Protein Structure and Function Prediction - Robert Ezra Langlois and Hui Lu
4. Modeling Protein-Protein and Protein-Nucleic Acid Interactions: Structure, Thermodynamics, and Kinetics - Huan-Xiang Zhou, Sanbo Qin and Harianto Tjong
5. Analysing Protein NMR pH-titration Curves - Jens Erik Nielsen
6. Implicit Solvent Simulations of Biomolecules in Cellular Environments - Michael Feig, Seiichiro Tanizaki, and Maryam Sayadi
Section 3: Simulation Methodologies (Section Editor: Carlos Simmerling)
7. Implicit Solvent Models in Molecular Dynamics Simulations: A Brief Overview - Alexey Onufriev
8. Comparing MD Simulations and NMR Relaxation Parameters - Vance Wong and David A. Case
1. Structural Perspectives on Protein Evolution - Eric Franzosa and Yu Xia
2. Predicting Selectivity and Druggability in Drug Discovery - Alan C. Cheng
Section 2: Biological Modeling (Section Editor: Nathan Barker)
3. Machine Learning for Protein Structure and Function Prediction - Robert Ezra Langlois and Hui Lu
4. Modeling Protein-Protein and Protein-Nucleic Acid Interactions: Structure, Thermodynamics, and Kinetics - Huan-Xiang Zhou, Sanbo Qin and Harianto Tjong
5. Analysing Protein NMR pH-titration Curves - Jens Erik Nielsen
6. Implicit Solvent Simulations of Biomolecules in Cellular Environments - Michael Feig, Seiichiro Tanizaki, and Maryam Sayadi
Section 3: Simulation Methodologies (Section Editor: Carlos Simmerling)
7. Implicit Solvent Models in Molecular Dynamics Simulations: A Brief Overview - Alexey Onufriev
8. Comparing MD Simulations and NMR Relaxation Parameters - Vance Wong and David A. Case