BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

224 related articles for article (PubMed ID: 24500199)

  • 1. A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data.
    Orenstein Y; Shamir R
    Nucleic Acids Res; 2014 Apr; 42(8):e63. PubMed ID: 24500199
    [TBL] [Abstract][Full Text] [Related]  

  • 2. BEESEM: estimation of binding energy models using HT-SELEX data.
    Ruan S; Swamidass SJ; Stormo GD
    Bioinformatics; 2017 Aug; 33(15):2288-2295. PubMed ID: 28379348
    [TBL] [Abstract][Full Text] [Related]  

  • 3. High-Throughput Protein Production Combined with High- Throughput SELEX Identifies an Extensive Atlas of Ciona robusta Transcription Factor DNA-Binding Specificities.
    Nitta KR; Vincentelli R; Jacox E; Cimino A; Ohtsuka Y; Sobral D; Satou Y; Cambillau C; Lemaire P
    Methods Mol Biol; 2019; 2025():487-517. PubMed ID: 31267468
    [TBL] [Abstract][Full Text] [Related]  

  • 4. High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions.
    Agius P; Arvey A; Chang W; Noble WS; Leslie C
    PLoS Comput Biol; 2010 Sep; 6(9):. PubMed ID: 20838582
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Quantitative modeling of transcription factor binding specificities using DNA shape.
    Zhou T; Shen N; Yang L; Abe N; Horton J; Mann RS; Bussemaker HJ; Gordân R; Rohs R
    Proc Natl Acad Sci U S A; 2015 Apr; 112(15):4654-9. PubMed ID: 25775564
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluating a linear k-mer model for protein-DNA interactions using high-throughput SELEX data.
    Kähärä J; Lähdesmäki H
    BMC Bioinformatics; 2013; 14 Suppl 10(Suppl 10):S2. PubMed ID: 24267147
    [TBL] [Abstract][Full Text] [Related]  

  • 7. RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and structure information.
    Ishida R; Adachi T; Yokota A; Yoshihara H; Aoki K; Nakamura Y; Hamada M
    Nucleic Acids Res; 2020 Aug; 48(14):e82. PubMed ID: 32537639
    [TBL] [Abstract][Full Text] [Related]  

  • 8. High-throughput sequencing SELEX for the determination of DNA-binding protein specificities in vitro.
    Pantier R; Chhatbar K; Alston G; Lee HY; Bird A
    STAR Protoc; 2022 Sep; 3(3):101490. PubMed ID: 35776646
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SELEX-Seq: A Method to Determine DNA Binding Specificities of Plant Transcription Factors.
    Smaczniak C; Angenent GC; Kaufmann K
    Methods Mol Biol; 2017; 1629():67-82. PubMed ID: 28623580
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A systematic, large-scale comparison of transcription factor binding site models.
    Hombach D; Schwarz JM; Robinson PN; Schuelke M; Seelow D
    BMC Genomics; 2016 May; 17():388. PubMed ID: 27209209
    [TBL] [Abstract][Full Text] [Related]  

  • 11. FSBC: fast string-based clustering for HT-SELEX data.
    Kato S; Ono T; Minagawa H; Horii K; Shiratori I; Waga I; Ito K; Aoki T
    BMC Bioinformatics; 2020 Jun; 21(1):263. PubMed ID: 32580745
    [TBL] [Abstract][Full Text] [Related]  

  • 12. DNA-binding specificities of human transcription factors.
    Jolma A; Yan J; Whitington T; Toivonen J; Nitta KR; Rastas P; Morgunova E; Enge M; Taipale M; Wei G; Palin K; Vaquerizas JM; Vincentelli R; Luscombe NM; Hughes TR; Lemaire P; Ukkonen E; Kivioja T; Taipale J
    Cell; 2013 Jan; 152(1-2):327-39. PubMed ID: 23332764
    [TBL] [Abstract][Full Text] [Related]  

  • 13. HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models.
    Kulakovskiy IV; Vorontsov IE; Yevshin IS; Soboleva AV; Kasianov AS; Ashoor H; Ba-Alawi W; Bajic VB; Medvedeva YA; Kolpakov FA; Makeev VJ
    Nucleic Acids Res; 2016 Jan; 44(D1):D116-25. PubMed ID: 26586801
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Using protein-binding microarrays to study transcription factor specificity: homologs, isoforms and complexes.
    Andrilenas KK; Penvose A; Siggers T
    Brief Funct Genomics; 2015 Jan; 14(1):17-29. PubMed ID: 25431149
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence.
    Wang J
    BMC Bioinformatics; 2014 Aug; 15(1):289. PubMed ID: 25158938
    [TBL] [Abstract][Full Text] [Related]  

  • 16. SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics.
    Chen D; Orenstein Y; Golodnitsky R; Pellach M; Avrahami D; Wachtel C; Ovadia-Shochat A; Shir-Shapira H; Kedmi A; Juven-Gershon T; Shamir R; Gerber D
    Sci Rep; 2016 Sep; 6():33351. PubMed ID: 27628341
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery.
    Hoinka J; Berezhnoy A; Dao P; Sauna ZE; Gilboa E; Przytycka TM
    Nucleic Acids Res; 2015 Jul; 43(12):5699-707. PubMed ID: 25870409
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A widespread role of the motif environment in transcription factor binding across diverse protein families.
    Dror I; Golan T; Levy C; Rohs R; Mandel-Gutfreund Y
    Genome Res; 2015 Sep; 25(9):1268-80. PubMed ID: 26160164
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Conservation and regulatory associations of a wide affinity range of mouse transcription factor binding sites.
    Jaeger SA; Chan ET; Berger MF; Stottmann R; Hughes TR; Bulyk ML
    Genomics; 2010 Apr; 95(4):185-95. PubMed ID: 20079828
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray.
    Wong KC; Li Y; Peng C; Wong HS
    IEEE/ACM Trans Comput Biol Bioinform; 2016; 13(2):261-71. PubMed ID: 27045826
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.