Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 106

1.

Functional-network-based gene set analysis using gene-ontology.

Chang B, Kustra R, Tian W.

PLoS One. 2013;8(2):e55635. doi: 10.1371/journal.pone.0055635. Epub 2013 Feb 13.

2.

Gene networks in Drosophila melanogaster: integrating experimental data to predict gene function.

Costello JC, Dalkilic MM, Beason SM, Gehlhausen JR, Patwardhan R, Middha S, Eads BD, Andrews JR.

Genome Biol. 2009;10(9):R97. doi: 10.1186/gb-2009-10-9-r97. Epub 2009 Sep 16.

3.

GObar: a gene ontology based analysis and visualization tool for gene sets.

Lee JS, Katari G, Sachidanandam R.

BMC Bioinformatics. 2005 Jul 25;6:189.

5.

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

Samsonova AA, Niranjan M, Russell S, Brazma A.

PLoS Comput Biol. 2007 Jul;3(7):e144.

6.

In silico gene function prediction using ontology-based pattern identification.

Zhou Y, Young JA, Santrosyan A, Chen K, Yan SF, Winzeler EA.

Bioinformatics. 2005 Apr 1;21(7):1237-45. Epub 2004 Nov 5.

PMID:
15531612
7.

Knowledge-guided multi-scale independent component analysis for biomarker identification.

Chen L, Xuan J, Wang C, Shih IeM, Wang Y, Zhang Z, Hoffman E, Clarke R.

BMC Bioinformatics. 2008 Oct 6;9:416. doi: 10.1186/1471-2105-9-416.

8.

Down-weighting overlapping genes improves gene set analysis.

Tarca AL, Draghici S, Bhatti G, Romero R.

BMC Bioinformatics. 2012 Jun 19;13:136. doi: 10.1186/1471-2105-13-136.

9.

Exploring tomato gene functions based on coexpression modules using graph clustering and differential coexpression approaches.

Fukushima A, Nishizawa T, Hayakumo M, Hikosaka S, Saito K, Goto E, Kusano M.

Plant Physiol. 2012 Apr;158(4):1487-502. doi: 10.1104/pp.111.188367. Epub 2012 Feb 3.

10.

Improving gene set analysis of microarray data by SAM-GS.

Dinu I, Potter JD, Mueller T, Liu Q, Adewale AJ, Jhangri GS, Einecke G, Famulski KS, Halloran P, Yasui Y.

BMC Bioinformatics. 2007 Jul 5;8:242.

11.

A transversal approach to predict gene product networks from ontology-based similarity.

Chabalier J, Mosser J, Burgun A.

BMC Bioinformatics. 2007 Jul 2;8:235.

12.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

Martini P, Risso D, Sales G, Romualdi C, Lanfranchi G, Cagnin S.

BMC Bioinformatics. 2011 Apr 11;12:92. doi: 10.1186/1471-2105-12-92.

13.

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

Dong X, Hao Y, Wang X, Tian W.

Sci Rep. 2016 Jan 11;6:18871. doi: 10.1038/srep18871.

14.

Construction and analysis of an integrated regulatory network derived from high-throughput sequencing data.

Cheng C, Yan KK, Hwang W, Qian J, Bhardwaj N, Rozowsky J, Lu ZJ, Niu W, Alves P, Kato M, Snyder M, Gerstein M.

PLoS Comput Biol. 2011 Nov;7(11):e1002190. doi: 10.1371/journal.pcbi.1002190. Epub 2011 Nov 17.

15.

A network-based gene-weighting approach for pathway analysis.

Fang Z, Tian W, Ji H.

Cell Res. 2012 Mar;22(3):565-80. doi: 10.1038/cr.2011.149. Epub 2011 Sep 6.

16.

Using pathway signatures as means of identifying similarities among microarray experiments.

Beltrame L, Rizzetto L, Paola R, Rocca-Serra P, Gambineri L, Battaglia C, Cavalieri D.

PLoS One. 2009;4(1):e4128. doi: 10.1371/journal.pone.0004128. Epub 2009 Jan 6.

17.

Comment on 'Network-constrained regularization and variable selection for analysis of genomic data'.

Binder H, Schumacher M.

Bioinformatics. 2008 Nov 1;24(21):2566-8; author reply 2569. doi: 10.1093/bioinformatics/btn412. Epub 2008 Aug 4. No abstract available.

PMID:
18682424
18.

NET-GE: a novel NETwork-based Gene Enrichment for detecting biological processes associated to Mendelian diseases.

Di Lena P, Martelli PL, Fariselli P, Casadio R.

BMC Genomics. 2015;16 Suppl 8:S6. doi: 10.1186/1471-2164-16-S8-S6. Epub 2015 Jun 18.

19.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

Kadupitige SR, Leung KC, Sellmeier J, Sivieng J, Catchpoole DR, Bain ME, Gaƫta BA.

BMC Genomics. 2009 Dec 3;10 Suppl 3:S17. doi: 10.1186/1471-2164-10-S3-S17.

20.

Gene set enrichment meta-learning analysis: next- generation sequencing versus microarrays.

Stiglic G, Bajgot M, Kokol P.

BMC Bioinformatics. 2010 Apr 8;11:176. doi: 10.1186/1471-2105-11-176.

Supplemental Content

Support Center