title: Letting the data speak for themselves: a fully  Bayesian approach to transcriptome assembly.
abstract: A novel method for transcriptome assembly, Bayesembler, provides greater accuracy without sacrifice of computational speed, and particular advantages for alternative transcripts expressed at low levels.
authors.affiliation: Excellence Cluster for Multimodal Computing and Interaction, Saarland 66123, Germany. mschulz@mmci.uni-saarland.de
authors.forename: Marcel H
authors.initials: MH
authors.lastname: Schulz
mesh_terms: D001499:Bayes Theorem; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D012984:Software; D059467:Transcriptome
references.citation: Nat Biotechnol. 2010 May;28(5):511-5
references.pmid: 20436464
references.citation: J Comput Biol. 2011 Nov;18(11):1693-707
references.pmid: 21951053
references.citation: Bioinformatics. 2012 Nov 15;28(22):2914-21
references.pmid: 23060617
references.citation: Genome Res. 2013 Mar;23(3):519-29
references.pmid: 23204306
references.citation: BMC Bioinformatics. 2013;14 Suppl 5:S15
references.pmid: 23734627
references.citation: Bioinformatics. 2013 Oct 15;29(20):2529-38
references.pmid: 23980025
references.citation: Nat Methods. 2013 Dec;10(12):1177-84
references.pmid: 24185837
references.citation: Bioinformatics. 2014 Sep 1;30(17):2447-55
references.pmid: 24813214
references.citation: Genome Biol. 2014;15(10):501
references.pmid: 25367074