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Finding regulatory elements using joint likelihoods for sequence and expression profile data

I Holmes, W J Bruno
2000 Proceedings. International Conference on Intelligent Systems for Molecular Biology  
We present a likelihood function for a "sequence-expression" model giving a joint likelihood for a promoter sequence and its corresponding expression levels.  ...  A recent, popular method of finding promoter sequences is to look for conserved motifs upstream of genes clustered on the basis of expression data.  ...  and Roger Sayle. We would like to thank Oli Bye for providing web hosting services for downloading of the kimono program and the Santa Fe Institute for providing additional computing resources.  ... 
pmid:10977081 fatcat:cfwx4sf3ljecta7whygqgpxoey

Combining Sequence and Time Series Expression Data to Learn Transcriptional Modules

A. Kundaje, M. Middendorf, Feng Gao, C. Wiggins, C. Leslie
2005 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
Thus, the algorithm gives a global approach for associating sets of regulatory elements to "modules" of genes with similar time series expression profiles.  ...  We present * Corresponding author a generative probabilistic model for combining regulatory sequence and time series expression data to cluster genes into coherent transcriptional modules.  ...  [22] : starting with occurrence data of putative regulatory elements and a time series expression profile for each gene, we present a probabilistic model for combining the regulatory sequence and expression  ... 
doi:10.1109/tcbb.2005.34 pmid:17044183 fatcat:zc7hok2hj5arlaewxafsl6j3ju

Pathway Modeling: New face of Graphical Probabilistic Analysis

Somnath Tagore, Virendra S. Gomase, Rajat K. De
2008 Journal of Proteomics & Bioinformatics  
Graphical probabilistic approaches are one of the unique methodologies that are used for designing and analyzing pathways.  ...  Various modeling problems of diseases can be successfully analyzed using this simulation approach.  ...  Latent Variable Models (LVM) is used for studying various regulatory networks, pathway modeling and gene expression profiles.  ... 
doi:10.4172/jpb.1000035 fatcat:jcoxyyn3bfh6zhd3zhauwq6rhu

A novel parametric approach to mine gene regulatory relationship from microarray datasets

Wanlin Liu, Dong Li, Qijun Liu, Yunping Zhu, Fuchu He
2010 BMC Bioinformatics  
Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively.  ...  Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data.  ...  The positive likelihood ratio is a good option, for it could indicate the probability of the existence of the existing regulatory relationship and be used for integration of the parameters with Bayesian  ... 
doi:10.1186/1471-2105-11-s11-s15 pmid:21172050 pmcid:PMC3024862 fatcat:l2qcdmbduvaa5fms6yv727ei4q

Allegro: Analyzing expression and sequence in concert to discover regulatory programs

Yonit Halperin, Chaim Linhart, Igor Ulitsky, Ron Shamir
2009 Nucleic Acids Research  
We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3' UTR sequences.  ...  Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis.  ...  Funding for open access charge: ISF 802/08 and 1767.07.  ... 
doi:10.1093/nar/gkn1064 pmid:19151090 pmcid:PMC2655690 fatcat:wnec4q7eazgixooji7etzmljzq

dSreg: A bayesian model to integrate changes in splicing and RNA binding protein activity [article]

Carlos Martí-Gómez, Enrique Lara-Pezzi, Fátima Sánchez-Cabo
2019 bioRxiv   pre-print
We developed a bayesian model that integrates RNA-seq and regulatory elements data to simultaneously infer changes in inclusion rates and in the activity of the underlying regulators.  ...  Here, we examined the influence of different sequencing depths in the identification of regulatory patterns of AS using simulated data with traditional workflows, showing poor performance and high dependence  ...  ACKNOWLEDGEMENTS We would like to thank Victor Jimenez for critical reading and useful discussions about the manuscript and beyond.  ... 
doi:10.1101/595751 fatcat:jdu3aconzreotmnz7lom4453va

Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition

U. Ohler, H. Niemann, G.-c. Liao, G. M. Rubin
2001 Bioinformatics  
The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel.  ...  In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties.  ...  The authors wish to thank Georg Stemmer for helpful comments on the paper. Uwe Ohler is a fellow of the Boehringer Ingelheim Fonds. Gerald Rubin was supported by the Howard Hughes Medical Institute.  ... 
doi:10.1093/bioinformatics/17.suppl_1.s199 pmid:11473010 fatcat:w7qmtmccjrf3tbla3p7rbh35mm

Genome-wide discovery of transcriptional modules from DNA sequence and gene expression

E. Segal, R. Yelensky, D. Koller
2003 Bioinformatics  
In this paper, we describe an approach for understanding transcriptional regulation from both gene expression and promoter sequence data.  ...  Using the EM algorithm, our approach refines both the module assignment and the motif profile so as to best explain the expression data as a function of transcriptional motifs.  ...  First, we use both expression and sequence data together, requiring that modules display a coherent profile for both.  ... 
doi:10.1093/bioinformatics/btg1038 pmid:12855470 fatcat:ida35n6vvzfonasr7opzjk4zni

MotifPrototyper: A Bayesian profile model for motif families

E. P. Xing, R. M. Karp
2004 Proceedings of the National Academy of Sciences of the United States of America  
, motif parameter estimation and de novo motif detection using the learned profile models.  ...  Each family corresponds to transcription regulatory proteins with similar types of structural signatures in their DNA binding domains.  ...  showed that these more expressive motif models lead to better likelihood scores for motifs, and can improve the sensitivity and specificity of motif detection in yeast regulatory sequences under a simple  ... 
doi:10.1073/pnas.0403564101 pmid:15252200 pmcid:PMC489970 fatcat:vhexymchqbhrnfzwxd2dh67tsu

Computational Approaches to Identify Promoters and cis-Regulatory Elements in Plant Genomes

S. Rombauts
2003 Plant Physiology  
However, due to differences in sequence content, the parameters used to detect CpG islands in humans and other vertebrates cannot be used for plants.  ...  Here, we review the different approaches that have been developed for identifying promoters and their regulatory elements.  ...  ACKNOWLEDGEMENTS We thank two anonymous reviewers for helpful suggestions.  ... 
doi:10.1104/pp.102.017715 pmid:12857799 pmcid:PMC167057 fatcat:m62u6wxzp5cn7fsaxxrbweqtru

Recent Computational Approaches to Understand Gene Regulation: Mining Gene Regulation In Silico

I. Abnizova, T. Subhankulova, W. Gilks
2007 Current Genomics  
Integration of genome sequences and/or Chromatin Immunoprecipitation on chip data with gene-expression data has facilitated in silico discovery of how the combinatorics and positioning of transcription  ...  We will consider the following computational areas: o gene regulatory network construction; o evolution of regulatory DNA; o studies of its structural and statistical informational properties; o and finally  ...  ACKNOWLEDGEMENTS We are thankful to Graham Ellis for support and to Rene te Boekhorst for hard work with references.  ... 
doi:10.2174/138920207780368150 pmid:18660846 pmcid:PMC2435357 fatcat:ztr3u3c42zazzdp6ug4pwy5l54

Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements

Fiona Allum, Åsa K. Hedman, Xiaojian Shao, Warren A. Cheung, Jinchu Vijay, Frédéric Guénard, Tony Kwan, Marie-Michelle Simon, Bing Ge, Cristiano Moura, Elodie Boulier, Lars Rönnblom (+8 others)
2019 Nature Communications  
at regulatory elements.  ...  Here we apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal~400), providing high-resolution methylation profiling (>1.3 M CpGs)  ...  Data availability The methylation and expression data from the MuTHER cohort have been deposited in the ArrayExpress, (accession no.  ... 
doi:10.1038/s41467-019-09184-z pmid:30872577 pmcid:PMC6418220 fatcat:hakd4gawwfc3diwdu27cjyxnsy

Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease

Christopher A. Odhams, Deborah S. Cunninghame Graham, Timothy J. Vyse, Tuuli Lappalainen
2017 PLoS Genetics  
After stringently testing for a shared causal variant using both the Joint Likelihood Mapping and 24 Regulatory Trait Concordance frameworks, we found that gene-level quantification significantly 25 underestimated  ...  We make use of 46 existing RNA-Seq expression data profiled at gene-, isoform-, exon-, junction-, and intron-level, and 47 perform eQTL analysis using association data from twenty autoimmune diseases.  ...  JLIM: joint likelihood mapping.  ... 
doi:10.1371/journal.pgen.1007071 pmid:29059182 pmcid:PMC5695635 fatcat:hml7zvos6rcpnclvpnw5uup3se

Computational Identification of Active Enhancers in Model Organisms

Chengqi Wang, Michael Q. Zhang, Zhihua Zhang
2013 Genomics, Proteomics & Bioinformatics  
Although experimental technologies have been developed to identify enhancers genome-wide, the design principle of the regulatory elements and the way they rewire the transcriptional regulatory network  ...  Enhancers can regulate gene expression in a cell-type specific and developmental stage specific manner.  ...  The two scores (LLR1 and LLR2) compare the likelihood of a sequence under the MORPH model to the likelihood of the sequences under null models.  ... 
doi:10.1016/j.gpb.2013.04.002 pmid:23685394 pmcid:PMC4357786 fatcat:siti7l62qnghnb4es26fsecdam

Extensive low-affinity transcriptional interactions in the yeast genome

A. Tanay
2006 Genome Research  
Pe'er, and E. Siggia for discussions and critical reading of the manuscript; three anonymous referees for comments; and the Rothschild foundation for support.  ...  Testing quantitative ChIP-sequence correlation ChIP data and PWM predictions for each TF were combined to generate a two-dimensional joint distribution.  ...  Transcriptional programs are commonly described via the identification of cis-elements in gene regulatory regions and their association with sequence-specific transcription factors (TFs).  ... 
doi:10.1101/gr.5113606 pmid:16809671 pmcid:PMC1524868 fatcat:fbqcmvtpkjcspk53peyly4skfu
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