Introduction to Protein Structure Prediction (eBook)

DR. HUZEFA RANGWALA is an assistant professor in computer science and bioengineering at George Mason University. He has published in various conferences and journals on the topic of bioinformatics. DR. GEORGE KARYPIS is a professor in computer science and engineering at the University of Minnesota. He has authored more than one hundred journal and conference papers and also serves on the editorial board of the International Journal of Data Mining and Bioinformatics.

Preface.

Contributors.

1 Introduction to Protein Structure Prediction (Huzefa
Rangwala and George Karypis).

2 CASP: A Driving Force in Protein Structure Modeling
(Andriy Kryshtafovych, Krzysztof Fidelis, and John
Moult).

3 The Protein Structure Initiative (Andras Fiser, Adam
Godzik, Christine Orengo, and Burkhard Rost).

4 Prediction of One-Dimensional Structural Properties of
Proteins by Integrated Neural Networks (Yaoqi Zhou and Eshel
Faraggi).

5 Local Structure Alphabets (Agnel Praveen Joseph,
Aurélie Bornot, and Alexandre G. de Brevern).

6 Shedding Light on Transmembrane Topology (Gábor
E. Tusnády and István Simon).

7 Contact Map Prediction by Machine Learning (Alberto
J.M. Martin, Catherine Mooney, Ian Walsh, and Gianluca
Pollastri).

8 A Survey of Remote Homology Detection and Fold Recognition
Methods (Huzefa Rangwala).

9 Interactive Protein Fold Recognition by Alignments and
Machine Learning (Allison N. Tegge, Zheng Wang, and Jianlin
Cheng).

10 Tasser-Based Protein Structure Prediction (Shashi
Bhushan Pandit, Hongyi Zhou, and Jeffrey Skolnick).

11 Composite Approaches to Protein Tertiary Structure
Prediction: A Case-Study by I-Tasser (Ambrish Roy, Sitao Wu,
and Yang Zhang).

12 Hybrid Methods for Protein Structure Prediction
(Dmitri Mourado, Bostjan Kobe, Nicholas E. Dixon, and Thomas
Huber).

13 Modeling Loops in Protein Structures (Narcis
Fernandez-Fuentes, Andras Fiser).

14 Model Quality Assessment Using A Statistical Program that
Adopts A Side Chain Environment Viewpoint (Genki Terashi,
Mayuko Takeda-Shitaka, Kazuhiko Kanou and Hideaki Umeyama).

15 Model Quality Prediction (Liam J.
McGuffin).

16 Ligand-Binding Residue Prediction (Chris Kauffman
and George Karypis).

17 Modeling and Validation of Transmembrane Protein
Structures (Maya Schushan and Nir Ben-Tal).

18 Structure-Based Machine Learning Models for Computational
Mutagenesis (Majid Masso and Iosif I. Vaisman).

19 Conformational Search for the Protein Native State
(Amarda Shehu).

20 Modeling Mutations in Proteins Using MEDUSA and Discrete
Molecule Dynamics (Shuangye Yin, Feng Ding, and Nikolay V.
Dokholyan).

Index.