Integrative Protein Fold Recognition by Alignments and Machine Learning

Allison N Tegge; Zheng Wang; Jianlin Cheng

doi:10.1002/9780470882207.ch9

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Book chapter

Integrative Protein Fold Recognition by Alignments and Machine Learning

Allison N Tegge, Zheng Wang and Jianlin Cheng

Introduction to Protein Structure Prediction, pp.195-218

John Wiley & Sons, Inc

2010-11-12

DOI: https://doi.org/10.1002/9780470882207.ch9

Abstract

machine learning fold recognition methods ‐ meta approach for fold recognition

machine learning methods, more advanced useful features ‐ needed for addressing fold recognition problem

integrative protein fold recognition by alignments and machine learning ‐ 3D structure prediction and template‐based approach

This chapter contains sections titled: Introduction Alignment Fold Recognition Methods Machine Learning Fold Recognition Methods Conclusions Acknowledgments References

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Title: Integrative Protein Fold Recognition by Alignments and Machine Learning
Creators: Allison N Tegge - Computer Science Department and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
Zheng Wang - Computer Science Department and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
Jianlin Cheng - Computer Science Department and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
Contributors: Huzefa Rangwala (Editor) - Department of Computer Science, George Mason University, Fairfax, VA 22030, USA
George Karypis (Editor) - Department of Computer Science, University of Minnesota Minneapolis, MN 55455, USA
Publication Details: Introduction to Protein Structure Prediction, pp.195-218
Publisher: John Wiley & Sons, Inc; Hoboken, NJ, USA
Number of pages: 24
Academic Unit: College of A&S; A&S - Computer Science
Language: English
Resource Type: Book chapter
Record Identifier: 991031600637702976