Literature DB >> 16597250

A practical approach to significance assessment in alignment with gaps.

Nicholas Chia1, Ralf Bundschuh.   

Abstract

Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

Mesh:

Year:  2006        PMID: 16597250     DOI: 10.1089/cmb.2006.13.429

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  3 in total

1.  New finite-size correction for local alignment score distributions.

Authors:  Yonil Park; Sergey Sheetlin; Ning Ma; Thomas L Madden; John L Spouge
Journal:  BMC Res Notes       Date:  2012-06-12

2.  A probabilistic model of local sequence alignment that simplifies statistical significance estimation.

Authors:  Sean R Eddy
Journal:  PLoS Comput Biol       Date:  2008-05-30       Impact factor: 4.475

Review 3.  Metabolic modeling with Big Data and the gut microbiome.

Authors:  Jaeyun Sung; Vanessa Hale; Annette C Merkel; Pan-Jun Kim; Nicholas Chia
Journal:  Appl Transl Genom       Date:  2016-02-05
  3 in total

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