Chapter: Chapter 3 - Machine Learning for Protein Structure and Function Prediction

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Home > Annual Reports in Computational Chemistry > Chapter 3 - Machine Learning for Protein Structure and Function Prediction

Annual Reports in Computational Chemistry |

Ralph A. Wheeler; David C. Spellmeyer

Elsevier

Annual Reports in Computational Chemistry

Chapter 3 - Machine Learning for Protein Structure and Function Prediction

Chapter Info

Authors

Robert Ezra Langlois; Hui Lu

ARI Id

1665573095466_17321220

Access

Open/Free Access

Pages

41-66

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Chapters/Headings	Author(s)	Pages	Info
Series Page		iii
Copyright		iv
Contents		v-viii
Contributors		ix-xi
Preface to Volume 4		xiii
Section 1: Bioinformatics
Section Editor: Wei Wang		1
Chapter 1 - Structural Perspectives on Protein Evolution	Eric Franzosa; Yu Xia	3-21
Chapter 2 - Predicting Selectivity and Druggability in Drug Discovery	Alan C. Cheng	23-37
Section 2: Biological Modeling
Section Editor: Nathan Baker		39
Chapter 3 - Machine Learning for Protein Structure and Function Prediction	Robert Ezra Langlois; Hui Lu	41-66
Chapter 4 - Modeling Protein–Protein and Protein–Nucleic Acid Interactions: Structure, Thermodynamics, and Kinetics	Huan-Xiang Zhou; Sanbo Qin; Harianto Tjong	67-87
Chapter 5 - Analyzing Protein NMR pH-Titration Curves	Jens Erik Nielsen	89-106
Chapter 6 - Implicit Solvent Simulations of Biomolecules in Cellular Environments	Michael Feig; Seiichiro Tanizaki; Maryam Sayadi	107-121
Section 3: Simulation Methodologies
Section Editor: Carlos Simmerling		123
Chapter 7 - Implicit Solvent Models in Molecular Dynamics Simulations: A Brief Overview	Alexey Onufriev	125-137
Chapter 8 - Comparing MD Simulations and NMR Relaxation Parameters	Vance Wong; David A. Case	139-154
Chapter 9 - Applications and Advances of QM/MM Methods in Computational Enzymology	Alessio Lodola; Christopher J. Woods; Adrian J. Mulholland	155-169
Chapters/Headings	Author(s)	Pages	Info

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