272 related articles for article (PubMed ID: 26108437)
1. Multiobjective triclustering of time-series transcriptome data reveals key genes of biological processes.
Bhar A; Haubrock M; Mukhopadhyay A; Wingender E
BMC Bioinformatics; 2015 Jun; 16():200. PubMed ID: 26108437
[TBL] [Abstract][Full Text] [Related]
2. Triclustering method for finding biomarkers in human immunodeficiency virus-1 gene expression data.
Siswantining T; Bustamam A; Sarwinda D; Soemartojo SM; Latief MA; Octaria EA; Siregar ATM; Septa O; Al-Ash HS; Saputra N
Math Biosci Eng; 2022 May; 19(7):6743-6763. PubMed ID: 35730281
[TBL] [Abstract][Full Text] [Related]
3. THD-Tricluster: A robust triclustering technique and its application in condition specific change analysis in HIV-1 progression data.
Kakati T; Ahmed HA; Bhattacharyya DK; Kalita JK
Comput Biol Chem; 2018 Aug; 75():154-167. PubMed ID: 29787933
[TBL] [Abstract][Full Text] [Related]
4. Coexpression and coregulation analysis of time-series gene expression data in estrogen-induced breast cancer cell.
Bhar A; Haubrock M; Mukhopadhyay A; Maulik U; Bandyopadhyay S; Wingender E
Algorithms Mol Biol; 2013 Mar; 8(1):9. PubMed ID: 23521829
[TBL] [Abstract][Full Text] [Related]
5. TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.
Jung I; Jo K; Kang H; Ahn H; Yu Y; Kim S
Bioinformatics; 2017 Dec; 33(23):3827-3835. PubMed ID: 28096084
[TBL] [Abstract][Full Text] [Related]
6. Transcriptome analysis in cardiomyocyte-specific differentiation of murine embryonic stem cells reveals transcriptional regulation network.
Gan L; Schwengberg S; Denecke B
Gene Expr Patterns; 2014 Sep; 16(1):8-22. PubMed ID: 25058891
[TBL] [Abstract][Full Text] [Related]
7. TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search.
Biswal BS; Patra S; Mohapatra A; Vipsita S
IET Syst Biol; 2020 Dec; 14(6):323-333. PubMed ID: 33399096
[TBL] [Abstract][Full Text] [Related]
8. Comparative transcriptomic analysis identifies genes differentially expressed in human epicardial progenitors and hiPSC-derived cardiac progenitors.
Synnergren J; Drowley L; Plowright AT; Brolén G; Goumans MJ; Gittenberger-de Groot AC; Sartipy P; Wang QD
Physiol Genomics; 2016 Nov; 48(11):771-784. PubMed ID: 27591124
[TBL] [Abstract][Full Text] [Related]
9. A new method of finding groups of coexpressed genes and conditions of coexpression.
Anand R; Ravichandran S; Chatterjee S
BMC Bioinformatics; 2016 Nov; 17(1):486. PubMed ID: 27887568
[TBL] [Abstract][Full Text] [Related]
10. Constructing temporal regulatory cascades in the context of development and cell differentiation.
Daou R; Beißbarth T; Wingender E; Gültas M; Haubrock M
PLoS One; 2020; 15(4):e0231326. PubMed ID: 32275727
[TBL] [Abstract][Full Text] [Related]
11. Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes.
Chou JW; Zhou T; Kaufmann WK; Paules RS; Bushel PR
BMC Bioinformatics; 2007 Nov; 8():427. PubMed ID: 17980031
[TBL] [Abstract][Full Text] [Related]
12. Discovering monotonic stemness marker genes from time-series stem cell microarray data.
Wang HW; Sun HJ; Chang TY; Lo HH; Cheng WC; Tseng GC; Lin CT; Chang SJ; Pal N; Chung IF
BMC Genomics; 2015; 16 Suppl 2(Suppl 2):S2. PubMed ID: 25708300
[TBL] [Abstract][Full Text] [Related]
13. Time-dependent evolution of functional vs. remodeling signaling in induced pluripotent stem cell-derived cardiomyocytes and induced maturation with biomechanical stimulation.
Jung G; Fajardo G; Ribeiro AJ; Kooiker KB; Coronado M; Zhao M; Hu DQ; Reddy S; Kodo K; Sriram K; Insel PA; Wu JC; Pruitt BL; Bernstein D
FASEB J; 2016 Apr; 30(4):1464-79. PubMed ID: 26675706
[TBL] [Abstract][Full Text] [Related]
14. A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes.
Grancharova T; Gerbin KA; Rosenberg AB; Roco CM; Arakaki JE; DeLizo CM; Dinh SQ; Donovan-Maiye RM; Hirano M; Nelson AM; Tang J; Theriot JA; Yan C; Menon V; Palecek SP; Seelig G; Gunawardane RN
Sci Rep; 2021 Aug; 11(1):15845. PubMed ID: 34349150
[TBL] [Abstract][Full Text] [Related]
15. Biclustering of microarray data with MOSPO based on crowding distance.
Liu J; Li Z; Hu X; Chen Y
BMC Bioinformatics; 2009 Apr; 10 Suppl 4(Suppl 4):S9. PubMed ID: 19426457
[TBL] [Abstract][Full Text] [Related]
16. Unsupervised analysis of whole transcriptome data from human pluripotent stem cells cardiac differentiation.
P Agostinho S; A Branco M; E S Nogueira D; Diogo MM; S Cabral JM; N Fred AL; V Rodrigues CA
Sci Rep; 2024 Feb; 14(1):3110. PubMed ID: 38326387
[TBL] [Abstract][Full Text] [Related]
17. G-Tric: generating three-way synthetic datasets with triclustering solutions.
Lobo J; Henriques R; Madeira SC
BMC Bioinformatics; 2021 Jan; 22(1):16. PubMed ID: 33413095
[TBL] [Abstract][Full Text] [Related]
18. Exploring matrix factorization techniques for significant genes identification of Alzheimer's disease microarray gene expression data.
Kong W; Mou X; Hu X
BMC Bioinformatics; 2011; 12 Suppl 5(Suppl 5):S7. PubMed ID: 21989140
[TBL] [Abstract][Full Text] [Related]
19. CXCL4/PF4 is a predictive biomarker of cardiac differentiation potential of human induced pluripotent stem cells.
Ohashi F; Miyagawa S; Yasuda S; Miura T; Kuroda T; Itoh M; Kawaji H; Ito E; Yoshida S; Saito A; Sameshima T; Kawai J; Sawa Y; Sato Y
Sci Rep; 2019 Mar; 9(1):4638. PubMed ID: 30874579
[TBL] [Abstract][Full Text] [Related]
20. Global transcriptome analysis of murine embryonic stem cell-derived cardiomyocytes.
Doss MX; Winkler J; Chen S; Hippler-Altenburg R; Sotiriadou I; Halbach M; Pfannkuche K; Liang H; Schulz H; Hummel O; Hübner N; Rottscheidt R; Hescheler J; Sachinidis A
Genome Biol; 2007; 8(4):R56. PubMed ID: 17428332
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]