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Items: 1 to 20 of 144

1.

LSTrAP: efficiently combining RNA sequencing data into co-expression networks.

Proost S, Krawczyk A, Mutwil M.

BMC Bioinformatics. 2017 Oct 10;18(1):444. doi: 10.1186/s12859-017-1861-z.

2.

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

Johnson BK, Scholz MB, Teal TK, Abramovitch RB.

BMC Bioinformatics. 2016 Feb 4;17:66. doi: 10.1186/s12859-016-0923-y.

3.

MOROKOSHI: transcriptome database in Sorghum bicolor.

Makita Y, Shimada S, Kawashima M, Kondou-Kuriyama T, Toyoda T, Matsui M.

Plant Cell Physiol. 2015 Jan;56(1):e6. doi: 10.1093/pcp/pcu187. Epub 2014 Dec 9.

4.

CATchUP: A Web Database for Spatiotemporally Regulated Genes.

Nakamura Y, Kudo T, Terashima S, Saito M, Nambara E, Yano K.

Plant Cell Physiol. 2017 Jan 1;58(1):e3. doi: 10.1093/pcp/pcw199.

PMID:
28013273
5.

From Gigabyte to Kilobyte: A Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data.

Li J, Hou J, Sun L, Wilkins JM, Lu Y, Niederhuth CE, Merideth BR, Mawhinney TP, Mossine VV, Greenlief CM, Walker JC, Folk WR, Hannink M, Lubahn DB, Birchler JA, Cheng J.

PLoS One. 2015 Apr 22;10(4):e0125000. doi: 10.1371/journal.pone.0125000. eCollection 2015.

6.

Functional annotation of the transcriptome of Sorghum bicolor in response to osmotic stress and abscisic acid.

Dugas DV, Monaco MK, Olsen A, Klein RR, Kumari S, Ware D, Klein PE.

BMC Genomics. 2011 Oct 18;12:514. doi: 10.1186/1471-2164-12-514.

7.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

Zhu M, Dahmen JL, Stacey G, Cheng J.

BMC Bioinformatics. 2013 Sep 22;14:278. doi: 10.1186/1471-2105-14-278.

8.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

Contreras-López O, Moyano TC, Soto DC, Gutiérrez RA.

Methods Mol Biol. 2018;1761:275-301. doi: 10.1007/978-1-4939-7747-5_21.

PMID:
29525965
9.

Falco: a quick and flexible single-cell RNA-seq processing framework on the cloud.

Yang A, Troup M, Lin P, Ho JW.

Bioinformatics. 2017 Mar 1;33(5):767-769. doi: 10.1093/bioinformatics/btw732.

PMID:
28025200
10.

Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana.

Giorgi FM, Del Fabbro C, Licausi F.

Bioinformatics. 2013 Mar 15;29(6):717-24. doi: 10.1093/bioinformatics/btt053. Epub 2013 Feb 1.

PMID:
23376351
11.

EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data.

Li J, Bushel PR.

BMC Genomics. 2016 Mar 22;17:255. doi: 10.1186/s12864-016-2584-7.

12.

Identification of regulatory modules in genome scale transcription regulatory networks.

Song Q, Grene R, Heath LS, Li S.

BMC Syst Biol. 2017 Dec 15;11(1):140. doi: 10.1186/s12918-017-0493-2.

13.

Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size.

Guo W, Calixto CPG, Tzioutziou N, Lin P, Waugh R, Brown JWS, Zhang R.

BMC Syst Biol. 2017 Jun 19;11(1):62. doi: 10.1186/s12918-017-0440-2.

14.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.

Feltus FA, Ficklin SP, Gibson SM, Smith MC.

BMC Syst Biol. 2013 Jun 5;7:44. doi: 10.1186/1752-0509-7-44.

15.

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

Yu H, Jiao B, Lu L, Wang P, Chen S, Liang C, Liu W.

PLoS One. 2018 Feb 9;13(2):e0192613. doi: 10.1371/journal.pone.0192613. eCollection 2018.

16.

A component overlapping attribute clustering (COAC) algorithm for single-cell RNA sequencing data analysis and potential pathobiological implications.

Peng H, Zeng X, Zhou Y, Zhang D, Nussinov R, Cheng F.

PLoS Comput Biol. 2019 Feb 19;15(2):e1006772. doi: 10.1371/journal.pcbi.1006772. eCollection 2019 Feb.

17.

Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data.

Paulson JN, Chen CY, Lopes-Ramos CM, Kuijjer ML, Platig J, Sonawane AR, Fagny M, Glass K, Quackenbush J.

BMC Bioinformatics. 2017 Oct 3;18(1):437. doi: 10.1186/s12859-017-1847-x.

18.

VCNet: vector-based gene co-expression network construction and its application to RNA-seq data.

Wang Z, Fang H, Tang NL, Deng M.

Bioinformatics. 2017 Jul 15;33(14):2173-2181. doi: 10.1093/bioinformatics/btx131.

PMID:
28334366
19.

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

Gardeux V, David FPA, Shajkofci A, Schwalie PC, Deplancke B.

Bioinformatics. 2017 Oct 1;33(19):3123-3125. doi: 10.1093/bioinformatics/btx337.

20.

PlaNet: Comparative Co-Expression Network Analyses for Plants.

Proost S, Mutwil M.

Methods Mol Biol. 2017;1533:213-227.

PMID:
27987173

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