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dc.contributor.authorHadzipasic, Omar
dc.contributor.authorWrabl, James O.
dc.contributor.authorHilser, Vincent J.
dc.date.accessioned2014-04-04T15:09:42Z
dc.date.available2014-04-04T15:09:42Z
dc.date.issued2013-10-10
dc.identifier.citationdoi: 10.1371/journal.pcbi.1003247en_US
dc.identifier.issn1553-734X
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/36747
dc.descriptionPMC3794901en_US
dc.description.abstractAn algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed numerical sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit gap penalties. Additionally, an empirical probability model is developed to estimate the significance of the returned alignment with respect to randomized data. The algorithm's utility for biological hypothesis formulation is demonstrated with test cases including database search and pairwise alignment of protein hydropathy. However, the algorithm and probability model could possibly be extended to accommodate other diverse types of protein or nucleic acid data, including positional thermodynamic stability and mRNA translation efficiency. The algorithm requires only numerical values as input and will readily compare data other than protein hydropathy. The tool is therefore expected to complement, rather than replace, existing sequence and structure based tools and may inform medical discovery, as exemplified by proposed similarity between a chlamydial ORFan protein and bacterial colicin pore-forming domain. The source code, documentation, and a basic web-server application are available.en_US
dc.description.sponsorshipJH Libraries Open Access Funden_US
dc.language.isoen_USen_US
dc.publisherPLoS Organizationen_US
dc.relation.ispartofseriesPLoS Computational Biology;v. 9 no. 10 p. e1003247
dc.subjectMembrane structuresen_US
dc.subjectMembrane proteinsen_US
dc.subjectProtein sequencingen_US
dc.subjectProtein structureen_US
dc.subjectProtein structure predictionen_US
dc.subjectSequence alignmenten_US
dc.subjectSequence databasesen_US
dc.subjectSequence similarity searchingen_US
dc.titleA horizontal alignment tool for numerical trend discovery in sequence data: application to protein hydropathy.en_US
dc.typeArticleen_US


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