Literature DB >> 21300846

Maximally efficient modeling of DNA sequence motifs at all levels of complexity.

Gary D Stormo1.   

Abstract

Identification of transcription factor binding sites is necessary for deciphering gene regulatory networks. Several new methods provide extensive data about the specificity of transcription factors but most methods for analyzing these data to obtain specificity models are limited in scope by, for example, assuming additive interactions or are inefficient in their exploration of more complex models. This article describes an approach--encoding of DNA sequences as the vertices of a regular simplex--that allows simultaneous direct comparison of simple and complex models, with higher-order parameters fit to the residuals of lower-order models. In addition to providing an efficient assessment of all model parameters, this approach can yield valuable insight into the mechanism of binding by highlighting features that are critical to accurate models.

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Year:  2011        PMID: 21300846      PMCID: PMC3070529          DOI: 10.1534/genetics.110.126052

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  18 in total

Review 1.  DNA binding sites: representation and discovery.

Authors:  G D Stormo
Journal:  Bioinformatics       Date:  2000-01       Impact factor: 6.937

Review 2.  Is there a code for protein-DNA recognition? Probab(ilistical)ly. . .

Authors:  Panayiotis V Benos; Alan S Lapedes; Gary D Stormo
Journal:  Bioessays       Date:  2002-05       Impact factor: 4.345

Review 3.  Determining the specificity of protein-DNA interactions.

Authors:  Gary D Stormo; Yue Zhao
Journal:  Nat Rev Genet       Date:  2010-09-28       Impact factor: 53.242

4.  Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE.

Authors:  Barrett C Foat; Alexandre V Morozov; Harmen J Bussemaker
Journal:  Bioinformatics       Date:  2006-07-15       Impact factor: 6.937

Review 5.  Putting numbers on the network connections.

Authors:  Gary D Stormo; Yue Zhao
Journal:  Bioessays       Date:  2007-08       Impact factor: 4.345

6.  Analysis of distribution of bases in the coding sequences by a diagrammatic technique.

Authors:  C T Zhang; R Zhang
Journal:  Nucleic Acids Res       Date:  1991-11-25       Impact factor: 16.971

7.  Displaying the information contents of structural RNA alignments: the structure logos.

Authors:  J Gorodkin; L J Heyer; S Brunak; G D Stormo
Journal:  Comput Appl Biosci       Date:  1997-12

8.  A weight array method for splicing signal analysis.

Authors:  M Q Zhang; T G Marr
Journal:  Comput Appl Biosci       Date:  1993-10

9.  Inferring binding energies from selected binding sites.

Authors:  Yue Zhao; David Granas; Gary D Stormo
Journal:  PLoS Comput Biol       Date:  2009-12-04       Impact factor: 4.475

10.  A feature-based approach to modeling protein-DNA interactions.

Authors:  Eilon Sharon; Shai Lubliner; Eran Segal
Journal:  PLoS Comput Biol       Date:  2008-08-22       Impact factor: 4.475

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  16 in total

1.  Improved models for transcription factor binding site identification using nonindependent interactions.

Authors:  Yue Zhao; Shuxiang Ruan; Manishi Pandey; Gary D Stormo
Journal:  Genetics       Date:  2012-04-13       Impact factor: 4.562

2.  Modeling the specificity of protein-DNA interactions.

Authors:  Gary D Stormo
Journal:  Quant Biol       Date:  2013-06

3.  On the sparsity of fitness functions and implications for learning.

Authors:  David H Brookes; Amirali Aghazadeh; Jennifer Listgarten
Journal:  Proc Natl Acad Sci U S A       Date:  2022-01-04       Impact factor: 12.779

4.  Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme.

Authors:  Gloria Yang; Dave W Anderson; Florian Baier; Elias Dohmen; Nansook Hong; Paul D Carr; Shina Caroline Lynn Kamerlin; Colin J Jackson; Erich Bornberg-Bauer; Nobuhiko Tokuriki
Journal:  Nat Chem Biol       Date:  2019-10-21       Impact factor: 15.040

5.  Defining the DNA uptake specificity of naturally competent Haemophilus influenzae cells.

Authors:  Joshua Chang Mell; Ira M Hall; Rosemary J Redfield
Journal:  Nucleic Acids Res       Date:  2012-06-29       Impact factor: 16.971

6.  Recognition models to predict DNA-binding specificities of homeodomain proteins.

Authors:  Ryan G Christensen; Metewo Selase Enuameh; Marcus B Noyes; Michael H Brodsky; Scot A Wolfe; Gary D Stormo
Journal:  Bioinformatics       Date:  2012-06-15       Impact factor: 6.937

7.  Assessing the effects of symmetry on motif discovery and modeling.

Authors:  Lala M Motlhabi; Gary D Stormo
Journal:  PLoS One       Date:  2011-09-20       Impact factor: 3.240

8.  Quantitative analysis demonstrates most transcription factors require only simple models of specificity.

Authors:  Yue Zhao; Gary D Stormo
Journal:  Nat Biotechnol       Date:  2011-06-07       Impact factor: 54.908

9.  Intermolecular epistasis shaped the function and evolution of an ancient transcription factor and its DNA binding sites.

Authors:  Dave W Anderson; Alesia N McKeown; Joseph W Thornton
Journal:  Elife       Date:  2015-06-15       Impact factor: 8.140

10.  The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis.

Authors:  Dave W Anderson; Florian Baier; Gloria Yang; Nobuhiko Tokuriki
Journal:  Nat Commun       Date:  2021-06-23       Impact factor: 14.919

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