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Items: 1 to 20 of 139

1.

Interpolative multidimensional scaling techniques for the identification of clusters in very large sequence sets.

Hughes A, Ruan Y, Ekanayake S, Bae SH, Dong Q, Rho M, Qiu J, Fox G.

BMC Bioinformatics. 2012 Mar 13;13 Suppl 2:S9. doi: 10.1186/1471-2105-13-S2-S9.

2.

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment.

Nagar A, Hahsler M.

BMC Bioinformatics. 2013;14 Suppl 11:S2. doi: 10.1186/1471-2105-14-S11-S2.

3.

Multidimensional scaling for large genomic data sets.

Tzeng J, Lu HH, Li WH.

BMC Bioinformatics. 2008 Apr 4;9:179. doi: 10.1186/1471-2105-9-179.

4.

NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads.

Mysara M, Leys N, Raes J, Monsieurs P.

BMC Bioinformatics. 2015 Mar 15;16:88. doi: 10.1186/s12859-015-0520-5.

5.

DNACLUST: accurate and efficient clustering of phylogenetic marker genes.

Ghodsi M, Liu B, Pop M.

BMC Bioinformatics. 2011 Jun 30;12:271. doi: 10.1186/1471-2105-12-271.

6.

NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes.

DeSantis TZ Jr, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno YM, Phan R, Andersen GL.

Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W394-9.

7.

Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads.

Bartram AK, Lynch MD, Stearns JC, Moreno-Hagelsieb G, Neufeld JD.

Appl Environ Microbiol. 2011 Jun;77(11):3846-52. doi: 10.1128/AEM.02772-10. Erratum in: Appl Environ Microbiol. 2011 Aug;77(15):5569.

8.

Bios2mds: an R package for comparing orthologous protein families by metric multidimensional scaling.

Pelé J, Bécu JM, Abdi H, Chabbert M.

BMC Bioinformatics. 2012 Jun 15;13:133. doi: 10.1186/1471-2105-13-133.

9.

Comprehensive aligned sequence construction for automated design of effective probes (CASCADE-P) using 16S rDNA.

DeSantis TZ, Dubosarskiy I, Murray SR, Andersen GL.

Bioinformatics. 2003 Aug 12;19(12):1461-8.

10.

ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences.

Sun Y, Cai Y, Liu L, Yu F, Farrell ML, McKendree W, Farmerie W.

Nucleic Acids Res. 2009 Jun;37(10):e76. doi: 10.1093/nar/gkp285.

11.
12.

Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering.

Yooseph S, Li W, Sutton G.

BMC Bioinformatics. 2008 Apr 10;9:182. doi: 10.1186/1471-2105-9-182.

13.

Phoenix 2: a locally installable large-scale 16S rRNA gene sequence analysis pipeline with Web interface.

Soh J, Dong X, Caffrey SM, Voordouw G, Sensen CW.

J Biotechnol. 2013 Sep 20;167(4):393-403. doi: 10.1016/j.jbiotec.2013.07.004.

14.

Reliable classification of two-class cancer data using evolutionary algorithms.

Deb K, Raji Reddy A.

Biosystems. 2003 Nov;72(1-2):111-29.

PMID:
14642662
15.

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples.

Barb JJ, Oler AJ, Kim HS, Chalmers N, Wallen GR, Cashion A, Munson PJ, Ames NJ.

PLoS One. 2016 Feb 1;11(2):e0148047. doi: 10.1371/journal.pone.0148047.

16.
17.

Kalign--an accurate and fast multiple sequence alignment algorithm.

Lassmann T, Sonnhammer EL.

BMC Bioinformatics. 2005 Dec 12;6:298.

18.
19.

MISHIMA--a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data.

Kryukov K, Saitou N.

BMC Bioinformatics. 2010 Mar 18;11:142. doi: 10.1186/1471-2105-11-142.

20.

Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes.

Kim M, Morrison M, Yu Z.

J Microbiol Methods. 2011 Jan;84(1):81-7. doi: 10.1016/j.mimet.2010.10.020.

PMID:
21047533
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