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Items: 1 to 20 of 162

1.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing.

Xiong X, Frank DN, Robertson CE, Hung SS, Markle J, Canty AJ, McCoy KD, Macpherson AJ, Poussier P, Danska JS, Parkinson J.

PLoS One. 2012;7(4):e36009. doi: 10.1371/journal.pone.0036009.

2.

Functional Profiling of Unfamiliar Microbial Communities Using a Validated De Novo Assembly Metatranscriptome Pipeline.

Davids M, Hugenholtz F, Martins dos Santos V, Smidt H, Kleerebezem M, Schaap PJ.

PLoS One. 2016 Jan 12;11(1):e0146423. doi: 10.1371/journal.pone.0146423.

3.

A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets.

Leimena MM, Ramiro-Garcia J, Davids M, van den Bogert B, Smidt H, Smid EJ, Boekhorst J, Zoetendal EG, Schaap PJ, Kleerebezem M.

BMC Genomics. 2013 Aug 2;14:530. doi: 10.1186/1471-2164-14-530.

4.
5.

Preparation and metatranscriptomic analyses of host-microbe systems.

Hampton-Marcell JT, Moormann SM, Owens SM, Gilbert JA.

Methods Enzymol. 2013;531:169-85. doi: 10.1016/B978-0-12-407863-5.00009-5.

PMID:
24060121
6.

MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function.

Keegan KP, Glass EM, Meyer F.

Methods Mol Biol. 2016;1399:207-33. doi: 10.1007/978-1-4939-3369-3_13.

PMID:
26791506
7.

Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.

Berendzen J, Bruno WJ, Cohn JD, Hengartner NW, Kuske CR, McMahon BH, Wolinsky MA, Xie G.

BMC Res Notes. 2012 Aug 28;5:460. doi: 10.1186/1756-0500-5-460.

8.

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

Jiang Y, Xiong X, Danska J, Parkinson J.

Microbiome. 2016 Jan 12;4:2. doi: 10.1186/s40168-015-0146-x.

9.

Comparison of assembly algorithms for improving rate of metatranscriptomic functional annotation.

Celaj A, Markle J, Danska J, Parkinson J.

Microbiome. 2014 Oct 28;2:39. doi: 10.1186/2049-2618-2-39.

10.

Comparison of library preparation methods reveals their impact on interpretation of metatranscriptomic data.

Alberti A, Belser C, Engelen S, Bertrand L, Orvain C, Brinas L, Cruaud C, Giraut L, Da Silva C, Firmo C, Aury JM, Wincker P.

BMC Genomics. 2014 Oct 20;15:912. doi: 10.1186/1471-2164-15-912.

11.

Comparative analyses of two Geraniaceae transcriptomes using next-generation sequencing.

Zhang J, Ruhlman TA, Mower JP, Jansen RK.

BMC Plant Biol. 2013 Dec 29;13:228. doi: 10.1186/1471-2229-13-228.

12.

Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L.) Lam].

Tao X, Gu YH, Wang HY, Zheng W, Li X, Zhao CW, Zhang YZ.

PLoS One. 2012;7(4):e36234. doi: 10.1371/journal.pone.0036234.

13.

Sequencing and characterization of the guppy (Poecilia reticulata) transcriptome.

Fraser BA, Weadick CJ, Janowitz I, Rodd FH, Hughes KA.

BMC Genomics. 2011 Apr 20;12:202. doi: 10.1186/1471-2164-12-202.

14.

CPSS: a computational platform for the analysis of small RNA deep sequencing data.

Zhang Y, Xu B, Yang Y, Ban R, Zhang H, Jiang X, Cooke HJ, Xue Y, Shi Q.

Bioinformatics. 2012 Jul 15;28(14):1925-7. doi: 10.1093/bioinformatics/bts282.

15.

Efficient assembly and annotation of the transcriptome of catfish by RNA-Seq analysis of a doubled haploid homozygote.

Liu S, Zhang Y, Zhou Z, Waldbieser G, Sun F, Lu J, Zhang J, Jiang Y, Zhang H, Wang X, Rajendran KV, Khoo L, Kucuktas H, Peatman E, Liu Z.

BMC Genomics. 2012 Nov 5;13:595. doi: 10.1186/1471-2164-13-595.

16.

Resources and costs for microbial sequence analysis evaluated using virtual machines and cloud computing.

Angiuoli SV, White JR, Matalka M, White O, Fricke WF.

PLoS One. 2011;6(10):e26624. doi: 10.1371/journal.pone.0026624.

17.

Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities.

Stewart FJ, Sharma AK, Bryant JA, Eppley JM, DeLong EF.

Genome Biol. 2011;12(3):R26. doi: 10.1186/gb-2011-12-3-r26.

18.

In depth annotation of the Anopheles gambiae mosquito midgut transcriptome.

PadrĂ³n A, Molina-Cruz A, Quinones M, Ribeiro JM, Ramphul U, Rodrigues J, Shen K, Haile A, Ramirez JL, Barillas-Mury C.

BMC Genomics. 2014 Jul 29;15:636. doi: 10.1186/1471-2164-15-636.

19.

BeMADS1 is a key to delivery MADSs into nucleus in reproductive tissues-De novo characterization of Bambusa edulis transcriptome and study of MADS genes in bamboo floral development.

Shih MC, Chou ML, Yue JJ, Hsu CT, Chang WJ, Ko SS, Liao DC, Huang YT, Chen JJ, Yuan JL, Gu XP, Lin CS.

BMC Plant Biol. 2014 Jul 2;14:179. doi: 10.1186/1471-2229-14-179.

20.

Gene finding in metatranscriptomic sequences.

Ismail WM, Ye Y, Tang H.

BMC Bioinformatics. 2014;15 Suppl 9:S8. doi: 10.1186/1471-2105-15-S9-S8.

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