6533b834fe1ef96bd129d615

RESEARCH PRODUCT

SKINK: a web server for string kernel based kink prediction in α-helices

Andreas LundChristofer S. TautermannSabine C. MuellerBenny KneisslAndreas HildebrandtTim Seifert

subject

Statistics and ProbabilitySkinkWeb serverTheoretical computer scienceComputer scienceReal-time computingcomputer.software_genreBiochemistryProtein Structure SecondaryStructural bioinformaticsSoftwareSequence Analysis ProteinString kernelPosition (vector)Ball (mathematics)Molecular BiologyInternetSequencebiologybusiness.industryComputational BiologyProteinsbiology.organism_classificationComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsbusinesscomputerSoftware

description

Abstract Motivation: The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. Here, we present a new web server, called SKINK, for string kernel based kink prediction. Extending our previous study, we also annotate the most probable kink position in a given α-helix sequence. Availability and implementation: The SKINK web server is freely accessible at http://biows-inf.zdv.uni-mainz.de/skink. Moreover, SKINK is a module of the BALL software, also freely available at www.ballview.org. Contact:  benny.kneissl@roche.com

yearjournalcountryeditionlanguage
2014-02-14Bioinformatics
https://doi.org/10.1093/bioinformatics/btu096