230 related articles for article (PubMed ID: 21912677)
1. Tree-based position weight matrix approach to model transcription factor binding site profiles.
Bi Y; Kim H; Gupta R; Davuluri RV
PLoS One; 2011; 6(9):e24210. PubMed ID: 21912677
[TBL] [Abstract][Full Text] [Related]
2. Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data.
Dabrowski M; Dojer N; Krystkowiak I; Kaminska B; Wilczynski B
BMC Bioinformatics; 2015 May; 16():140. PubMed ID: 25927199
[TBL] [Abstract][Full Text] [Related]
3. EMQIT: a machine learning approach for energy based PWM matrix quality improvement.
Smolinska K; Pacholczyk M
Biol Direct; 2017 Aug; 12(1):17. PubMed ID: 28764727
[TBL] [Abstract][Full Text] [Related]
4. Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.
Levitsky VG; Kulakovskiy IV; Ershov NI; Oshchepkov DY; Makeev VJ; Hodgman TC; Merkulova TI
BMC Genomics; 2014 Jan; 15(1):80. PubMed ID: 24472686
[TBL] [Abstract][Full Text] [Related]
5. A novel method for improved accuracy of transcription factor binding site prediction.
Khamis AM; Motwalli O; Oliva R; Jankovic BR; Medvedeva YA; Ashoor H; Essack M; Gao X; Bajic VB
Nucleic Acids Res; 2018 Jul; 46(12):e72. PubMed ID: 29617876
[TBL] [Abstract][Full Text] [Related]
6. abc4pwm: affinity based clustering for position weight matrices in applications of DNA sequence analysis.
Ali O; Farooq A; Yang M; Jin VX; Bjørås M; Wang J
BMC Bioinformatics; 2022 Mar; 23(1):83. PubMed ID: 35240993
[TBL] [Abstract][Full Text] [Related]
7. Simultaneously learning DNA motif along with its position and sequence rank preferences through expectation maximization algorithm.
Zhang Z; Chang CW; Hugo W; Cheung E; Sung WK
J Comput Biol; 2013 Mar; 20(3):237-48. PubMed ID: 23461573
[TBL] [Abstract][Full Text] [Related]
8. A general pairwise interaction model provides an accurate description of in vivo transcription factor binding sites.
Santolini M; Mora T; Hakim V
PLoS One; 2014; 9(6):e99015. PubMed ID: 24926895
[TBL] [Abstract][Full Text] [Related]
9. Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data.
Eggeling R; Roos T; Myllymäki P; Grosse I
BMC Bioinformatics; 2015 Nov; 16():375. PubMed ID: 26552868
[TBL] [Abstract][Full Text] [Related]
10. Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment.
Worsley Hunt R; Mathelier A; Del Peso L; Wasserman WW
BMC Genomics; 2014 Jun; 15(1):472. PubMed ID: 24927817
[TBL] [Abstract][Full Text] [Related]
11. Optimized position weight matrices in prediction of novel putative binding sites for transcription factors in the Drosophila melanogaster genome.
Morozov VY; Ioshikhes IP
PLoS One; 2013; 8(8):e68712. PubMed ID: 23936309
[TBL] [Abstract][Full Text] [Related]
12. A DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites.
Yang J; Ramsey SA
Bioinformatics; 2015 Nov; 31(21):3445-50. PubMed ID: 26130577
[TBL] [Abstract][Full Text] [Related]
13. Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.
Karnik R; Beer MA
PLoS One; 2015; 10(10):e0140557. PubMed ID: 26465884
[TBL] [Abstract][Full Text] [Related]
14. The next generation of transcription factor binding site prediction.
Mathelier A; Wasserman WW
PLoS Comput Biol; 2013; 9(9):e1003214. PubMed ID: 24039567
[TBL] [Abstract][Full Text] [Related]
15. Variable structure motifs for transcription factor binding sites.
Reid JE; Evans KJ; Dyer N; Wernisch L; Ott S
BMC Genomics; 2010 Jan; 11():30. PubMed ID: 20074339
[TBL] [Abstract][Full Text] [Related]
16. Transcription Factor Information System (TFIS): A Tool for Detection of Transcription Factor Binding Sites.
Narad P; Kumar A; Chakraborty A; Patni P; Sengupta A; Wadhwa G; Upadhyaya KC
Interdiscip Sci; 2017 Sep; 9(3):378-391. PubMed ID: 27052996
[TBL] [Abstract][Full Text] [Related]
17. From binding motifs in ChIP-Seq data to improved models of transcription factor binding sites.
Kulakovskiy I; Levitsky V; Oshchepkov D; Bryzgalov L; Vorontsov I; Makeev V
J Bioinform Comput Biol; 2013 Feb; 11(1):1340004. PubMed ID: 23427986
[TBL] [Abstract][Full Text] [Related]
18. MethMotif: an integrative cell specific database of transcription factor binding motifs coupled with DNA methylation profiles.
Xuan Lin QX; Sian S; An O; Thieffry D; Jha S; Benoukraf T
Nucleic Acids Res; 2019 Jan; 47(D1):D145-D154. PubMed ID: 30380113
[TBL] [Abstract][Full Text] [Related]
19. A Fast Cluster Motif Finding Algorithm for ChIP-Seq Data Sets.
Zhang Y; Wang P
Biomed Res Int; 2015; 2015():218068. PubMed ID: 26236718
[TBL] [Abstract][Full Text] [Related]
20. Differential motif enrichment analysis of paired ChIP-seq experiments.
Lesluyes T; Johnson J; Machanick P; Bailey TL
BMC Genomics; 2014 Sep; 15(1):752. PubMed ID: 25179504
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]