RNA classification and structure prediction: Algorithms and case studies

Ling Zhong, Junilda Spirollari, Jason T.L. Wang, Dongrong Wen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents the state of the art of the protein structure prediction (PSP) problem from a computational science perspective. It reports major and latest findings concerning protein folding and focuses on ab initio computational approaches. Although they are the most challenging methods, they are also the most promising ones since they are applicable, in principle, to any protein whose sequence is known. The chapter evaluates ab initio methods in the latest competition and discusses both the computational and biological complexities that still hinder improvements. Nature has evolved proteins whose folding includes additional biological complexities which are rarely considered by any existing method. The chapter reviews four of these classes: Membrane proteins, proteins whose folding is chaperone assisted, proteins with more than one stable structure, and intrinsically unstructured proteins.

Original languageEnglish (US)
Title of host publicationBiological Knowledge Discovery Handbook
Subtitle of host publicationPreprocessing, Mining and Postprocessing of Biological Data
Publisherwiley
Pages685-702
Number of pages18
ISBN (Electronic)9781118617151
ISBN (Print)9781118853726
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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