IsoSVM--distinguishing isoforms and paralogs on the protein level

BMC Bioinformatics
Michael SpitzerGeorg Fuellen

Abstract

Recent progress in cDNA and EST sequencing is yielding a deluge of sequence data. Like database search results and proteome databases, this data gives rise to inferred protein sequences without ready access to the underlying genomic data. Analysis of this information (e.g. for EST clustering or phylogenetic reconstruction from proteome data) is hampered because it is not known if two protein sequences are isoforms (splice variants) or not (i.e. paralogs/orthologs). However, even without knowing the intron/exon structure, visual analysis of the pattern of similarity across the alignment of the two protein sequences is usually helpful since paralogs and orthologs feature substitutions with respect to each other, as opposed to isoforms, which do not. The IsoSVM tool introduces an automated approach to identifying isoforms on the protein level using a support vector machine (SVM) classifier. Based on three specific features used as input of the SVM classifier, it is possible to automatically identify isoforms with little effort and with an accuracy of more than 97%. We show that the SVM is superior to a radial basis function network and to a linear classifier. As an example application we use IsoSVM to estimate that a set of Xenopu...Continue Reading

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Citations

Sep 4, 2008·Journal of Bioinformatics and Computational Biology·Alexander E Ivliev, Marina G Sergeeva
Feb 19, 2015·Proceedings of the National Academy of Sciences of the United States of America·Ramya Purkanti, Mukund Thattai
May 13, 2020·Strahlentherapie und Onkologie : Organ der Deutschen Röntgengesellschaft ... [et al]·Martin KocherPhilipp Lohmann
Mar 3, 2020·Frontiers in Neurology·Philipp LohmannNorbert Galldiks
Jun 12, 2020·Methods : a Companion to Methods in Enzymology·Philipp LohmannKarl-Josef Langen
Jul 25, 2007·Chemical Reviews·Gert Lubec, Leila Afjehi-Sadat

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Software Mentioned

IsoSVM
CAP3
BLAST
MVIEW
Vmatch
fftnsi
MathType
PSIBLAST
MAFFT
SVMLight

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