Effective optimization algorithms for fragment-assembly based protein structure prediction.

Effective optimization algorithms for fragment-assembly based protein structure prediction. Research Abstract Details 

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Effective optimization algorithms for fragment-assembly based protein structure prediction. Abstract Text:

Kevin W Deronne,George Karypis,

Despite recent developments in protein structure prediction, an accurate new fold prediction algorithm remains elusive. One of the challenges facing current techniques is the size and complexity of the space containing possible structures for a query sequence. Traditionally, to explore this space fragment assembly approaches to new fold prediction have used stochastic optimization techniques. Here, we examine deterministic algorithms for optimizing scoring functions in protein structure prediction. Two previously unused techniques are applied to the problem, called the Greedy algorithm and the Hill-climbing (HC) algorithm. The main difference between the two is that the latter implements a technique to overcome local minima. Experiments on a diverse set of 276 proteins show that the HC algorithms consistently outperform existing approaches based on Simulated Annealing optimization (a traditional stochastic technique) in optimizing the root mean squared deviation between native and working structures.

Effective optimization algorithms for fragment-assembly based protein structure prediction. Publishing Authors By Initials

KW Deronne,G Karypis,

For similar investigative techniques: genetic techniques: sequence analysis: sequence analysis, protein research abstracts see: investigative techniques: genetic techniques: sequence analysis: sequence analysis, protein research

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Effective optimization algorithms for fragment-assembly based protein structure prediction. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Journal of bioinformatics and computational biolog

VOLUME: 5

Page Numbers: 335-52

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ISSN: 0219-7200

DAY: 3

MONTH: Apr

YEAR: 2007

Effective optimization algorithms for fragment-assembly based protein structure prediction. Information

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LANGUAGE: eng

NlmUniqueID: 101187344

Effective optimization algorithms for fragment-assembly based protein structure prediction. Keywords Mesh Terms:

KEYWORDS: Sequence Analysis, Protein

MESH TERMS: methods

Chemical & Substance for Abstract: Effective optimization algorithms for fragment-assembly based protein structure prediction. Information

Substance Name: Proteins

Registry Number: 0

Grant and Affiliation Information for Effective optimization algorithms for fragment-assembly based protein structure prediction.

AFFILIATION: Department of Computer Science & Engineering, Digital Technology Center, Army HPC Research Center, University of Minnesota, Minneapolis, MN 55455, USA. deronne@cs.umn.edu

Country: England

AGENCY: United States PHS

GRANT: RLM008713A

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MEDLINETA: J Bioinform Comput Biol

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