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000827020 0247_ $$a10.1007/978-3-319-74775-0$$2doi
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000827020 049__ $$aISEA
000827020 050_4 $$aQ342
000827020 08204 $$a572/.633$$223
000827020 1001_ $$aJana, Nanda Dulal.$$eauthor.
000827020 24512 $$aA Metaheuristic Approach to Protein Structure Prediction :$$bAlgorithms and Insights from Fitness Landscape Analysis /$$cby Nanda Dulal Jana, Swagatam Das, Jaya Sil.
000827020 264_1 $$aCham :$$bSpringer International Publishing :$$bImprint: Springer,$$c2018.
000827020 300__ $$a1 online resource (xxix, 220 pages) :$$billustrations.
000827020 336__ $$atext$$btxt$$2rdacontent
000827020 337__ $$acomputer$$bc$$2rdamedia
000827020 338__ $$aonline resource$$bcr$$2rdacarrier
000827020 347__ $$atext file$$bPDF$$2rda
000827020 4901_ $$aEmergence, Complexity and Computation,$$x2194-7287 ;$$v31
000827020 504__ $$aIncludes bibliographical references.
000827020 5050_ $$aMetaheuristic Protein Structure Prediction-An Overview -- Related Works -- Continuous Landscape Analysis using Random Walk Algorithm -- Landscape Characterization and Algorithms Selection for the PSP Problem -- The Levy distributed Parameter Adaptive Metaheuristic Algorithm for Protein Structure Prediction -- Protein Structure Prediction using Improved Variants of Metaheuristic Algorithms -- Hybrid Metaheuristic Approach for Protein Structure Prediction -- Conclusions and Future Research.
000827020 506__ $$aAccess limited to authorized users.
000827020 520__ $$aThis book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.
000827020 650_0 $$aEngineering.
000827020 650_0 $$aArtificial intelligence.
000827020 650_0 $$aProteins.
000827020 650_0 $$aComputational intelligence.
000827020 650_0 $$aComputational complexity.
000827020 7001_ $$aDas, Swagatam.$$eauthor.
000827020 7001_ $$aSil, Jaya.$$eauthor.
000827020 77608 $$iPrint version: $$z9783319747743
000827020 830_0 $$aEmergence, complexity and computation ;$$v31.
000827020 852__ $$bebk
000827020 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-74775-0$$zOnline Access$$91397441.1
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000827020 980__ $$aEBOOK
000827020 980__ $$aBIB
000827020 982__ $$aEbook
000827020 983__ $$aOnline
000827020 994__ $$a92$$bISE