Literature DB >> 18428693

Using MUMmer to identify similar regions in large sequence sets.

Arthur L Delcher1, Steven L Salzberg, Adam M Phillippy.   

Abstract

The MUMmer sequence alignment package is a suite of computer programs designed to detect regions of homology in long biological sequences. Version 2.1 makes several improvements to the package, including: increased speed and reduced memory requirements; the ability to handle both protein and DNA sequences; the ability to handle multiple sequence fragments; and new algorithms for clustering together basic matches. The system is particularly efficient at comparing highly similar sequences, such as alternative versions of fragment assemblies or closely related strains of the same bacterium.

Mesh:

Year:  2003        PMID: 18428693     DOI: 10.1002/0471250953.bi1003s00

Source DB:  PubMed          Journal:  Curr Protoc Bioinformatics        ISSN: 1934-3396


  249 in total

1.  Genomic comparison of multi-drug resistant invasive and colonizing Acinetobacter baumannii isolated from diverse human body sites reveals genomic plasticity.

Authors:  Jason W Sahl; J Kristie Johnson; Anthony D Harris; Adam M Phillippy; William W Hsiao; Kerri A Thom; David A Rasko
Journal:  BMC Genomics       Date:  2011-06-04       Impact factor: 3.969

2.  A comparative genomic analysis of diverse clonal types of enterotoxigenic Escherichia coli reveals pathovar-specific conservation.

Authors:  Jason W Sahl; Hans Steinsland; Julia C Redman; Samuel V Angiuoli; James P Nataro; Halvor Sommerfelt; David A Rasko
Journal:  Infect Immun       Date:  2010-11-15       Impact factor: 3.441

3.  Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia.

Authors:  William C Nelson; Yukari Maezato; Yu-Wei Wu; Margaret F Romine; Stephen R Lindemann
Journal:  Appl Environ Microbiol       Date:  2015-10-23       Impact factor: 4.792

4.  Molecular analysis of asymptomatic bacteriuria Escherichia coli strain VR50 reveals adaptation to the urinary tract by gene acquisition.

Authors:  Scott A Beatson; Nouri L Ben Zakour; Makrina Totsika; Brian M Forde; Rebecca E Watts; Amanda N Mabbett; Jan M Szubert; Sohinee Sarkar; Minh-Duy Phan; Kate M Peters; Nicola K Petty; Nabil-Fareed Alikhan; Mitchell J Sullivan; Jayde A Gawthorne; Mitchell Stanton-Cook; Nguyen Thi Khanh Nhu; Teik Min Chong; Wai-Fong Yin; Kok-Gan Chan; Viktoria Hancock; David W Ussery; Glen C Ulett; Mark A Schembri
Journal:  Infect Immun       Date:  2015-02-09       Impact factor: 3.441

5.  Genomic and Phenotypic Diversity among Ten Laboratory Isolates of Pseudomonas aeruginosa PAO1.

Authors:  Courtney E Chandler; Alexander M Horspool; Preston J Hill; Daniel J Wozniak; Jeffrey W Schertzer; David A Rasko; Robert K Ernst
Journal:  J Bacteriol       Date:  2019-02-11       Impact factor: 3.490

6.  Insight into Energy Conservation via Alternative Carbon Monoxide Metabolism in Carboxydothermus pertinax Revealed by Comparative Genome Analysis.

Authors:  Yuto Fukuyama; Kimiho Omae; Yasuko Yoneda; Takashi Yoshida; Yoshihiko Sako
Journal:  Appl Environ Microbiol       Date:  2018-07-02       Impact factor: 4.792

7.  The genome sequence of the rumen methanogen Methanobrevibacter ruminantium reveals new possibilities for controlling ruminant methane emissions.

Authors:  Sinead C Leahy; William J Kelly; Eric Altermann; Ron S Ronimus; Carl J Yeoman; Diana M Pacheco; Dong Li; Zhanhao Kong; Sharla McTavish; Carrie Sang; Suzanne C Lambie; Peter H Janssen; Debjit Dey; Graeme T Attwood
Journal:  PLoS One       Date:  2010-01-28       Impact factor: 3.240

8.  New assembly, reannotation and analysis of the Entamoeba histolytica genome reveal new genomic features and protein content information.

Authors:  Hernan A Lorenzi; Daniela Puiu; Jason R Miller; Lauren M Brinkac; Paolo Amedeo; Neil Hall; Elisabet V Caler
Journal:  PLoS Negl Trop Dis       Date:  2010-06-15

9.  Phymm and PhymmBL: metagenomic phylogenetic classification with interpolated Markov models.

Authors:  Arthur Brady; Steven L Salzberg
Journal:  Nat Methods       Date:  2009-08-02       Impact factor: 28.547

10.  KISSa: a strategy to build multiple sequence alignments from pairwise comparisons of very closely related sequences.

Authors:  Francesco Marass; Chris Upton
Journal:  BMC Res Notes       Date:  2009-05-20
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