@article{Molineris2011,
    abstract = {{Changes in gene regulation are believed to play an important role in the evolution of animals. It has been suggested that changes in cis-regulatory regions are responsible for many or most of the anatomical and behavioral differences between humans and apes. However the study of the evolution of cis-regulatory regions is made problematic by the degeneracy of transcription factor binding sites and the shuffling of their positions. In this work we use the predicted total affinity of a promoter for a large collection of transcription factors as the basis to study the evolution of cis-regulatory regions in mammals. We introduce the human specificity of a promoter, measuring the divergence between the affinity profile of a human promoter and its orthologous promoters in other mammals. The promoters of genes involved in functional categories such as neural processes and signal transduction, among others, have higher human specificity compared to the rest of the genome. Clustering of the human-specific affinities of neural genes reveals patterns of promoter evolution associated to functional categories such as synaptic transmission and brain development, and to diseases such as bipolar disorder and autism}},
    author = {Molineris, I and Grassi, E and Ala, U and Di Cunto, F and Provero, P},
    citeulike-article-id = {8870649},
    citeulike-linkout-0 = {http://dx.doi.org/10.1093/molbev/msr027},
    citeulike-linkout-1 = {http://mbe.oxfordjournals.org/content/28/8/2173.abstract},
    citeulike-linkout-2 = {http://mbe.oxfordjournals.org/content/28/8/2173.full.pdf},
    citeulike-linkout-3 = {http://mbe.oxfordjournals.org/cgi/content/abstract/28/8/2173},
    citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/21335606},
    citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=21335606},
    day = {18},
    doi = {10.1093/molbev/msr027},
    issn = {1537-1719},
    journal = {Molecular Biology and Evolution},
    keywords = {eukaryote, evolution, gene\_regulation, human, promoter},
    month = feb,
    number = {8},
    pages = {2173--2183},
    pmid = {21335606},
    posted-at = {2011-07-27 16:23:57},
    priority = {2},
    title = {{Evolution of promoter affinity for transcription factors in the human lineage}},
    volume = {28},
    year = {2011}
}

@article{Foat2006,
abstract = {Regulation of gene expression by a transcription factor requires physical interaction between the factor and the DNA, which can be described by a statistical mechanical model. Based on this model, we developed the MatrixREDUCE algorithm, which uses genome-wide occupancy data for a transcription factor (e.g. ChIP-chip) and associated nucleotide sequences to discover the sequence-specific binding affinity of the transcription factor. Advantages of our approach are that the information for all probes on the microarray is efficiently utilized because there is no need to delineate "bound" and "unbound" sequences, and that, unlike information content-based methods, it does not require a background sequence model.},
author = {Foat, B C and Morozov, A V and Bussemaker, H J},
doi = {10.1093/bioinformatics/btl223},
file = {:home/data/Dropbox/work/articoli/tfbs/Bioinformatics-2006-Foat-e141-9.pdf:pdf},
issn = {1367-4811},
journal = {Bioinformatics (Oxford, England)},
keywords = {Algorithms,Base Sequence,Binding Sites,Biomechanics,Biomechanics: methods,Chromosome Mapping,Chromosome Mapping: methods,Computer Simulation,DNA,DNA: genetics,Models, Genetic,Models, Statistical,Molecular Sequence Data,Protein Binding,Sequence Alignment,Sequence Alignment: methods,Sequence Analysis, DNA,Sequence Analysis, DNA: methods,Software,Transcription Factors,Transcription Factors: genetics},
month = jul,
number = {14},
pages = {e141--9},
pmid = {16873464},
title = {{Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE.}},
volume = {22},
year = {2006}
}

@article{Bussemaker2008,
    abstract = {{Motivation: The identification of transcription factor (TF) binding sites and the regulatory circuitry that they define is currently an area of intense research. Data from whole-genome chromatin immunoprecipitation (ChIPâchip), whole-genome expression microarrays, and sequencing of multiple closely related genomes have all proven useful. By and large, existing methods treat the interpretation of functional data as a classification problem (between bound and unbound DNA), and the analysis of comparative data as a problem of local alignment (to recover phylogenetic footprints of presumably functional elements). Both of these approaches suffer from the inability to model and detect low-affinity binding sites, which have recently been shown to be abundant and functional.Results: We have developed a method that discovers functional regulatory targets of TFs by predicting the total affinity of each promoter for those factors and then comparing that affinity across orthologous promoters in closely related species. At each promoter, we consider the minimum affinity among orthologs to be the fraction of the affinity that is functional. Because we calculate the affinity of the entire promoter, our method is independent of local alignment. By comparing with functional annotation information and gene expression data in Saccharomyces cerevisiae, we have validated that this biophysically motivated use of evolutionary conservation gives rise to dramatic improvement in prediction of regulatory connectivity and factorâfactor interactions compared to the use of a single genome. We propose novel biological functions for several yeast TFs, including the factors Snt2 and Stb4, for which no function has been reported. Our affinity-based approach towards comparative genomics may allow a more quantitative analysis of the principles governing the evolution of non-coding DNA.Availability: The MatrixREDUCE software package is available from http://www.bussemakerlab.org/software/MatrixREDUCEContact: Harmen.Bussemaker@columbia.eduSupplementary information: Supplementary data are available at Bioinformatics online.}},
    author = {Ward, L D and Bussemaker, H J},
    booktitle = {Bioinformatics},
    citeulike-article-id = {2937498},
    citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btn154},
    citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/content/24/13/i165.abstract},
    citeulike-linkout-2 = {http://bioinformatics.oxfordjournals.org/content/24/13/i165.full.pdf},
    citeulike-linkout-3 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/24/13/i165},
    citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/18586710},
    citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=18586710},
    day = {1},
    doi = {10.1093/bioinformatics/btn154},
    journal = {Bioinformatics},
    keywords = {noalignment},
    month = jul,
    number = {13},
    pages = {i165--i171},
    pmid = {18586710},
    posted-at = {2008-06-27 15:59:14},
    priority = {2},
    title = {{Predicting functional transcription factor binding through alignment-free and affinity-based analysis of orthologous promoter sequences}},
    volume = {24},
    year = {2008}
}

 

@article{He2011,
author = {He, X and Duque, TS and Sinha, S},
file = {:home/data/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Access - 2011 - MBE Advance Access published November 10, 2011.pdf:pdf},
journal = {Molecular biology and evolution},
keywords = {complex genotypes,enhancer evolution,homotypic site clustering,thermodynamic},
pages = {1--34},
title = {{Evolutionary origins of transcription factor binding site clusters}},
year = {2011}
}
 
@article{Tanay2006,
    abstract = {{
                Major experimental and computational efforts are targeted at the characterization of transcriptional networks on a genomic scale. The ultimate goal of many of these studies is to construct networks associating transcription factors with genes via well-defined binding sites. Weaker regulatory interactions other than those occurring at high-affinity binding sites are largely ignored and are not well understood. Here I show that low-affinity interactions are abundant in vivo and quantifiable from current high-throughput ChIP experiments. I develop algorithms that predict DNA-binding energies from sequences and ChIP data across a wide dynamic range of affinities and use them to reveal widespread functionality of low-affinity transcription factor binding. Evolutionary analysis suggests that binding energies of many transcription factors are conserved even in promoters lacking classical binding sites. Gene expression analysis shows that such promoters can generate significant expression. I estimate that while only a small percentage of the genome is strongly regulated by a typical transcription factor, up to an order of magnitude more may be involved in weaker interactions. Low-affinity transcription factor-DNA interaction may therefore be important both evolutionarily and functionally.
            }},
    address = {Center for Studies in Physics and Biology, Rockefeller University, New York, New York 10021, USA.},
    author = {Tanay, A},
    citeulike-article-id = {767781},
    citeulike-linkout-0 = {http://dx.doi.org/10.1101/gr.5113606},
    citeulike-linkout-1 = {http://www.genome.org/cgi/content/abstract/16/8/962},
    citeulike-linkout-2 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1524868/},
    citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/16809671},
    citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=16809671},
    day = {29},
    doi = {10.1101/gr.5113606},
    issn = {1088-9051},
    journal = {Genome research},
    month = aug,
    number = {8},
    pages = {962--972},
    pmcid = {PMC1524868},
    pmid = {16809671},
    posted-at = {2011-12-14 18:30:59},
    priority = {2},
    title = {{Extensive low-affinity transcriptional interactions in the yeast genome.}},
    volume = {16},
    year = {2006}
}


