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Identifying transcription factor binding sites through Markov chain optimization

K. Ellrott, C. Yang, F. M. Sladek, T. Jiang
2002 Bioinformatics  
In this study, we have developed a computer algorithm to scan genomic databases for transcription factor binding sites, based on a novel Markov chain optimization method, and used it to scan the human  ...  A list of ¡ £ ¢ known HNF4 binding sites from the literature were used to train our Markov chain model.  ...  Carlotta Domeniconi (UCR) helped with debugging the Markov chain code, and Jim Kent (UCSC) provided tips on writing software to read the UCSC database.  ... 
doi:10.1093/bioinformatics/18.suppl_2.s100 pmid:12385991 fatcat:pfrdbhhsqvdlbd4vq5hjkyq6rq

STIF: Identification of stress-upregulated transcription factor binding sites in Arabidopsis thaliana

Ambika Shyam Sundar, Susan Mary Varghese, Khader Shameer, Nataraja Karaba, Makarla Udayakumar, Ramanathan Sowdhamini
2008 Bioinformation  
Hidden Markov models of the transcription factor binding sites enable the identification of predicted sites upstream of plant stress genes.  ...  factor binding sites upstream of a gene of interest.  ...  An HMM based method based on markov chain optimization is available for the identification of hepatocyte nuclear factor 4alpha in human genome [21] .  ... 
doi:10.6026/97320630002431 pmid:18841238 pmcid:PMC2561162 fatcat:u33u6dmrm5c3zcqxfeocnwvbna

Optimized mixed Markov models for motif identification

Weichun Huang, David M Umbach, Uwe Ohler, Leping Li
2006 BMC Bioinformatics  
Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challenging issue, largely due to limited availability  ...  Our optimized mixture of Markov models represents an alternative to the existing methods for modeling dependent structures within a biological motif.  ...  Variable Length Markov Model (PVLMM) for finding transcription factor binding sites and splice sites [24] .  ... 
doi:10.1186/1471-2105-7-279 pmid:16749929 pmcid:PMC1534070 fatcat:5prfexxvvnhurgsdlezczr273m

Finding short DNA motifs using permuted markov models

Xiaoyue Zhao, Haiyan Huang, Terence P. Speed
2004 Proceedings of the eighth annual international conference on Computational molecular biology - RECOMB '04  
Many short DNA motifs such as transcription factor binding sites (TFBS) and splice sites exhibit strong local as well as non-local dependence.  ...  We introduce permuted variable length Markov models (PVLMM) which could capture the potentially important dependencies among positions, and apply them to the problem of detecting splice and TFB sites.  ...  INTRODUCTION It is an important and also challenging task to identify short biological motifs such as transcription factor binding sites (TFBS) and splice sites, where the gene expression machinery interacts  ... 
doi:10.1145/974614.974624 dblp:conf/recomb/ZhaoHS04 fatcat:2bwfwmc5wranfoctb3geexzxke

Context dependent models for discovery of transcription factor binding sites

Chuancai Wang, Jun Xie, B.A. Craig
2006 Statistical Methodology  
Transcription factors play a crucial role in gene regulation, and the identification of transcription factor binding sites helps gain insight into gene regulatory mechanisms.  ...  ., binding sites) by a series of position-dependent first-order Markov models. This model considers both the position-specific features of the motif and the dependence between positions of the motif.  ...  The activated transcription factor binds to a short segment of DNA, known as a transcription factor binding site, and the RNA polymerase is then recruited to initiate the transcription of the gene.  ... 
doi:10.1016/j.stamet.2005.09.007 fatcat:mndlfncuzzfmxbnmktgbqomw7y

Beyond microarrays: Finding key transcription factors controlling signal transduction pathways

Alexdander Kel, Nico Voss, Ruy Jauregui, Olga Kel-Margoulis, Edgar Wingender
2006 BMC Bioinformatics  
We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways  ...  The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors.  ...  Transcription factors found by the downstream TFs -transcription factorsHMMs -Hidden Markov ModelsPWMs -positional weight matrices TFBS -transcription factor binding sites ...  ... 
doi:10.1186/1471-2105-7-s2-s13 pmid:17118134 pmcid:PMC1683568 fatcat:zdusg6vf2jhqzcknrr3cletlwy

Inclusion of neighboring base interdependencies substantially improves genome-wide prokaryotic transcription factor binding site prediction

R. A. Salama, D. J. Stekel
2010 Nucleic Acids Research  
Prediction of transcription factor binding sites is an important challenge in genome analysis.  ...  We have developed a novel training-based methodology intended for prokaryotic transcription factor binding site prediction.  ...  ACKNOWLEDGEMENTS The authors thank Steve Busby for his directions toward the choice of the binding sites; Joe Wade for help with the LexA data supplied; Nick Loman for help with the xBASE integration;  ... 
doi:10.1093/nar/gkq274 pmid:20439311 pmcid:PMC2896541 fatcat:cueaov4cvfeklkqdr2gvhafq34

A survey of DNA motif finding algorithms

Modan K Das, Ho-Kwok Dai
2007 BMC Bioinformatics  
An important task in this challenge is to identify regulatory elements, especially the binding sites in deoxyribonucleic acid (DNA) for transcription factors.  ...  These binding sites are short DNA segments that are called motifs.  ...  Identifying regulatory elements, especially the binding sites in DNA for transcription factors is a major task in this challenge.  ... 
doi:10.1186/1471-2105-8-s7-s21 pmid:18047721 pmcid:PMC2099490 fatcat:ngzr5j4puza2zfemvypdsxxhmq

Assessing Computational Methods of Cis-Regulatory Module Prediction

Jing Su, Sarah A. Teichmann, Thomas A. Down, Christina Leslie
2010 PLoS Computational Biology  
Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites  ...  For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs.  ...  transcription factor binding sites.  ... 
doi:10.1371/journal.pcbi.1001020 pmid:21152003 pmcid:PMC2996316 fatcat:p6yyjkliavd73cr67drf4ade6u

Parsing regulatory DNA: General tasks, techniques, and the PhyloGibbs approach

Rahul Siddharthan
2007 Journal of Biosciences  
Genes are transcriptionally regulated by specialised proteins (in particular, transcription factors, TFs) -a nomenclature we will use for any protein that binds to DNA and plays a regulatory role in the  ...  The main tasks we discuss are predicting local regions of DNA, cis-regulatory modules (CRMs) that contain binding sites for transcription factors (TFs), and predicting individ ual binding sites.  ... 
doi:10.1007/s12038-007-0086-0 pmid:17914228 fatcat:2v5md6ydmnb7rn57p7xygr5xqy

Computation-Based Discovery of Cis-Regulatory Modules by Hidden Markov Model

Jing Wu, Jun Xie
2008 Journal of Computational Biology  
In this article, we propose a hidden Markov model (HMM) to identify transcription factor binding sites (TFBSs) and cis-regulatory modules (CRMs).  ...  Each module contains multiple binding sites for a specific combination of several transcription factors.  ...  Recent studies suggest a modular organization of binding sites for transcription factors (Yuh et al. 1998 ).  ... 
doi:10.1089/cmb.2008.0024 pmid:18333759 fatcat:x5lekckninge7pabgc7adhkbdu

BoCaTFBS: a boosted cascade learner to refine the binding sites suggested by ChIP-chip experiments

Lu-yong Wang, Michael Snyder, Mark Gerstein
2006 Genome Biology  
Comprehensive mapping of transcription factor binding sites is essential in postgenomic biology.  ...  For this, we propose a mining approach combining noisy data from ChIP (chromatin immunoprecipitation)-chip experiments with known binding site patterns.  ...  An optimized Markov chain algorithm was introduced to integrate pair-wise correlation into Markov models to predict a partic-ular transcription factor's binding sites (hepatocyte nuclear factor 4α) [22  ... 
doi:10.1186/gb-2006-7-11-r102 pmid:17078876 pmcid:PMC1794589 fatcat:njcjy6s4hjb7xde4foj7s2dt4q

Recent Advances in the Computational Discovery of Transcription Factor Binding Sites

Tung Nguyen, Ioannis Androulakis
2009 Algorithms  
Computational inference of transcriptional regulatory networks from expression profiling and transcription factor binding site identification.  ...  These patterns, called motifs, are potential binding sites to transcription factors which are hypothesized to be the main regulators of the transcription process.  ...  Identifying transcription factor binding sites through Markov chain optimization. Bioinformatics 2002, 18 Suppl 2, S100-109. 43. Burge, C.; Karlin, S.  ... 
doi:10.3390/a2010582 fatcat:z3ijlhwgofbzjirnupglbtrf2e

Markov Encoding for Detecting Signals in Genomic Sequences

J.C. Rajapakse, Loi Sy Ho
2005 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
We demonstrate the efficacy of the Markov encoding method in the detection of three genomic signals, namely, splice sites, transcription start sites, and translation initiation sites.  ...  The encoding is based on lower-order Markov models which incorporate known biological characteristics in genomic sequences.  ...  Information in cells passes from DNA to mRNA to proteins through processes called transcription and translation.  ... 
doi:10.1109/tcbb.2005.27 pmid:17044178 fatcat:d3ffckjulra3ddwbridr5j2kca

NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequence

T. A. Down
2005 Nucleic Acids Research  
NestedMICA is a new, scalable, pattern-discovery system for finding transcription factor binding sites and similar motifs in biological sequences.  ...  When tested on a real set of regulatory sequences, NestedMICA produced motifs which were good predictors for all five abundant classes of annotated binding sites.  ...  One investigation of Markov chain backgrounds can be found in (15) : this concludes that pentanucleotide frequency tables (i.e. fourthorder Markov chains) are optimal.  ... 
doi:10.1093/nar/gki282 pmid:15760844 pmcid:PMC1064142 fatcat:w4isfcszpveajborvdl2ofr5ee
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