These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

267 related articles for article (PubMed ID: 19997485)

  • 1. Inferring binding energies from selected binding sites.
    Zhao Y; Granas D; Stormo GD
    PLoS Comput Biol; 2009 Dec; 5(12):e1000590. PubMed ID: 19997485
    [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. Better estimation of protein-DNA interaction parameters improve prediction of functional sites.
    Nagaraj VH; O'Flanagan RA; Sengupta AM
    BMC Biotechnol; 2008 Dec; 8():94. PubMed ID: 19105805
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Precise physical models of protein-DNA interaction from high-throughput data.
    Kinney JB; Tkacik G; Callan CG
    Proc Natl Acad Sci U S A; 2007 Jan; 104(2):501-6. PubMed ID: 17197415
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Inherent limitations of probabilistic models for protein-DNA binding specificity.
    Ruan S; Stormo GD
    PLoS Comput Biol; 2017 Jul; 13(7):e1005638. PubMed ID: 28686588
    [TBL] [Abstract][Full Text] [Related]  

  • 6. High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.
    Roulet E; Busso S; Camargo AA; Simpson AJ; Mermod N; Bucher P
    Nat Biotechnol; 2002 Aug; 20(8):831-5. PubMed ID: 12101405
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SAMIE: statistical algorithm for modeling interaction energies.
    Benos PV; Lapedes AS; Fields DS; Stormo GD
    Pac Symp Biocomput; 2001; ():115-26. PubMed ID: 11262933
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Probabilistic code for DNA recognition by proteins of the EGR family.
    Benos PV; Lapedes AS; Stormo GD
    J Mol Biol; 2002 Nov; 323(4):701-27. PubMed ID: 12419259
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding.
    Le DD; Shimko TC; Aditham AK; Keys AM; Longwell SA; Orenstein Y; Fordyce PM
    Proc Natl Acad Sci U S A; 2018 Apr; 115(16):E3702-E3711. PubMed ID: 29588420
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Structure-based ab initio prediction of transcription factor-binding sites.
    Liu LA; Bader JS
    Methods Mol Biol; 2009; 541():23-41. PubMed ID: 19381536
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Modeling DNA affinity landscape through two-round support vector regression with weighted degree kernels.
    Wang X; Kuwahara H; Gao X
    BMC Syst Biol; 2014; 8 Suppl 5(Suppl 5):S5. PubMed ID: 25605483
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Position dependencies in transcription factor binding sites.
    Tomovic A; Oakeley EJ
    Bioinformatics; 2007 Apr; 23(8):933-41. PubMed ID: 17308339
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Inferring protein-DNA interaction parameters from SELEX experiments.
    Djordjevic M
    Methods Mol Biol; 2010; 674():195-211. PubMed ID: 20827593
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Quantitative modeling and data analysis of SELEX experiments.
    Djordjevic M; Sengupta AM
    Phys Biol; 2005 Dec; 3(1):13-28. PubMed ID: 16582458
    [TBL] [Abstract][Full Text] [Related]  

  • 15. An equilibrium partitioning model connecting gene expression and cis-motif content.
    Mellor J; DeLisi C
    Bioinformatics; 2006 Jul; 22(14):e368-74. PubMed ID: 16873495
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively.
    Clifford J; Adami C
    Phys Biol; 2015 Sep; 12(5):056004. PubMed ID: 26331781
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Context specific transcription factor prediction.
    Yang E; Simcha D; Almon RR; Dubois DC; Jusko WJ; Androulakis IP
    Ann Biomed Eng; 2007 Jun; 35(6):1053-67. PubMed ID: 17377845
    [TBL] [Abstract][Full Text] [Related]  

  • 18. OHMM: a Hidden Markov Model accurately predicting the occupancy of a transcription factor with a self-overlapping binding motif.
    Drawid A; Gupta N; Nagaraj VH; GĂ©linas C; Sengupta AM
    BMC Bioinformatics; 2009 Jul; 10():208. PubMed ID: 19583839
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Ab initio prediction of transcription factor binding sites.
    Liu LA; Bader JS
    Pac Symp Biocomput; 2007; ():484-95. PubMed ID: 17990512
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Binding site graphs: a new graph theoretical framework for prediction of transcription factor binding sites.
    Reddy TE; DeLisi C; Shakhnovich BE
    PLoS Comput Biol; 2007 May; 3(5):e90. PubMed ID: 17500587
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.