Literature DB >> 10880857

A non-statistical approach to protein mutational variability.

J Leluk1.   

Abstract

The non-statistical, non-Markovian model of protein mutational variability is described. There are presented the essential features of the algorithm of genetic semihomology and some examples of its application. The results of genetic semihomology approach are compared with the results obtained by using statistical algorithms and matrices which are assumed in widely used programs such as ClustalW, FASTA, MultAlin and BLAST. The aim of the new algorithm elaboration is to improve the accuracy of the results of protein sequence comparison, avoid the wrong assumptions and misinterpretation of the results, and increase the amount of information available from such study.

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Year:  2000        PMID: 10880857     DOI: 10.1016/s0303-2647(00)00074-5

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  5 in total

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Journal:  Sci Rep       Date:  2021-05-05       Impact factor: 4.379

2.  Study on phylogenetic relationships, variability, and correlated mutations in M2 proteins of influenza virus A.

Authors:  Ly Le; Jacek Leluk
Journal:  PLoS One       Date:  2011-08-02       Impact factor: 3.240

3.  Comparative Study on Sequence-Structure-Function Relationship of the Human Short-chain Dehydrogenases/Reductases Protein Family.

Authors:  Nu Thi Ngoc Tang; Ly Le
Journal:  Evol Bioinform Online       Date:  2014-10-21       Impact factor: 1.625

4.  Acanthamoeba castellanii STAT protein.

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5.  Back-translation for discovering distant protein homologies in the presence of frameshift mutations.

Authors:  Marta Girdea; Laurent Noe; Gregory Kucherov
Journal:  Algorithms Mol Biol       Date:  2010-01-04       Impact factor: 1.405

  5 in total

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