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Comparison of human (and other) genome browsers

Terrence S Furey
2006 Human Genomics  
Furey Review SOFTWARER EVIEW The Ensembl browser contains the most extensives et of gene and transcription-related data, with 14 of its 22 Views primarily focused on the presentation of gene-or proteinrelated  ...  respect to presentation, contentand functionality.Presentation refers to howt he data ared isplayedi nagraphical forma nd the overall structure of the website.C ontentr eferst ow hat data is accessible,s  ... 
doi:10.1186/1479-7364-2-4-266 pmid:16460652 pmcid:PMC3525149 fatcat:534hbsoj4bfbfng3ihau6qqaqy

Correcting nucleotide-specific biases in high-throughput sequencing data

Jeremy R. Wang, Bryan Quach, Terrence S. Furey
2017 BMC Bioinformatics  
(Eq. 4). w t i = b S [i+t,i+t+k] f t S [i+t,i+t+k] (4) Per-tile weights are then aggregated according to the covariance groups.  ...  Throughout, we used the nucleotide sequence of the reference genome, S, to take into account bias outside the read boundaries.  ... 
doi:10.1186/s12859-017-1766-x pmid:28764645 pmcid:PMC5540620 fatcat:mgz6nzun5nhjnf7au27migcede

High-resolution mapping studies of chromatin and gene regulatory elements

Alan P Boyle, Terrence S Furey
2009 Epigenomics  
Microarray and high-throughput sequencing technologies have enabled the development of comprehensive assays to identify locations of particular chromatin structures and regulatory elements. It is now possible to create genome-wide maps of DNA methylation, trans-factor binding sites, histone variants and histone tail modifications, nucleosome positions, regions of open chromatin, and chromosome locations and interactions. This review provides a summary of these new assays that are changing the
more » ... y in which molecular biology research is being performed. While the generation of large amounts of data from these experiments is becoming increasingly easier, the development of corresponding analysis methods has progressed more slowly. It will likely be years before the full extent of the information contained in these data is fully appreciated. The rapid completion of the sequencing of many eukaryotic genomes is providing researchers with a necessary scaffold for advancing our knowledge of gene function and regulation. Annotating locations of transcribed protein-coding sequences within genomes has been a major initial focus, but simply knowing their locations does little to reveal just how their expression is regulated. The corresponding discovery of non-coding regulatory elements has lagged behind, owing to a much weaker or complete lack of signal in the primary DNA sequence. Previous attempts to identify regulatory elements have either focused on computational techniques to identify transcription factor binding sites and cis-regulatory modules, or were based on lower-throughput chromatin assays that looked at a small number of loci or functional assays that perturbed sequences within regulatory regions. Computational methods have a low specificity, producing many false-positives and providing no information about cell-specific or condition-specific regulation. Traditional wet laboratory experiments lack global sensitivity, since they were restricted to analyzing only small regions of the genome. Chromatin structure has been known to play a critical role in gene regulation. DNA accessibility, largely governed through the global and local positioning of nucleosomes, can be altered, preventing transcription factors from binding DNA; histones and their modifications
doi:10.2217/epi.09.29 pmid:20514362 pmcid:PMC2877397 fatcat:ppmllrxcdrdcteuipcnjhp6mc4

GSAASeqSP: A Toolset for Gene Set Association Analysis of RNA-Seq Data

Qing Xiong, Sayan Mukherjee, Terrence S. Furey
2014 Scientific Reports  
The indicator variables I(NAS(S j ,p) $ NAS(S i )), I(NAS(S j ) $ NAS(S i )), I(NAS(S j ,p) # NAS(S i )), and I(NAS(S j ) # NAS(S i )) equal 1 if NAS(S j ,p) $ NAS(S i ), NAS(S j ) $ NAS(S i ), NAS(S j  ...  ) and I(max j51,…,m NAS(S j ,p) # NAS(S i )) are 1 if max j51,…,m NAS(S j ,p) $ NAS(S i ) and max j51,…,m NAS(S j ,p) # NAS(S i ) respectively otherwise they are 0.  ... 
doi:10.1038/srep06347 pmid:25213199 pmcid:PMC4161965 fatcat:losj5hatorc3rpv2u3x6mtxami

DeFCoM: analysis and modeling of transcription factor binding sites using a motif-centric genomic footprinter

Bryan Quach, Terrence S. Furey
2016 Bioinformatics  
Inactive sites where s TF À s control > 0 were removed.  ...  The total number of windows k that will span a region of size s/2 can be calculated as follows: argmin k s 2 À g k ð Þ j s 2 À g k ð Þ !  ... 
doi:10.1093/bioinformatics/btw740 pmid:27993786 pmcid:PMC6075477 fatcat:gal7s2ar6jegde3fnx5gttzrsy

ChIP–seq and beyond: new and improved methodologies to detect and characterize protein–DNA interactions

Terrence S. Furey
2012 Nature reviews genetics  
| Chromatin immunoprecipitation experiments followed by sequencing (ChIPseq) detect protein-DNA binding events and chemical modifications of histone proteins. Challenges in the standard ChIP-seq protocol have motivated recent enhancements in this approach, such as reducing the number of cells that are required and increasing the resolution. Complementary experimental approaches -for example, DNaseI hypersensitive site mapping and analysis of chromatin interactions that are mediated by
more » ... proteins -provide additional information about DNA-binding proteins and their function. These data are now being used to identify variability in the functions of DNA-binding proteins across genomes and individuals. In this Review, I describe the latest advances in methods to detect and functionally characterize DNA-bound proteins.
doi:10.1038/nrg3306 pmid:23090257 pmcid:PMC3591838 fatcat:xslkppbbdbedzflqk6ir5wvqu4

Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation

Zhong Wang, Huntington F. Willard, Sayan Mukherjee, Terrence S. Furey
2006 PLoS Computational Biology  
Citation: Wang Z, Willard HF, Mukherjee S, Furey TS (2006) Evidence of influence of genomic DNA sequence on human X chromosome inactivation. PLoS Comput Biol 2(9): e113.  ...  It is possible that some of these features may serve as signals for some step(s) involved in the spread and/or maintenance of X inactivation.  ...  This establishes strong evidence that epigenetic regulation is, at least in part, dependent on genomic sequence and organization and provides a list of candidate sequence features whose role(s) in X inactivation  ... 
doi:10.1371/journal.pcbi.0020113 pmid:16948528 pmcid:PMC1557588 fatcat:u6n5crogofauja4r5gbqrgfcuy

Genetic and epigenetic determinants of inter-individual variability in responses to toxicants

Lauren Lewis, Gregory E. Crawford, Terrence S. Furey, Ivan Rusyn
2017 Current Opinion in Toxicology  
A common challenge among all regulatory element assays is determining the target gene(s) being regulated.  ... 
doi:10.1016/j.cotox.2017.08.006 pmid:29276797 pmcid:PMC5739339 fatcat:cegdvjoe2vb7pmaaoyajdh43qq

Genome-wide sequence and functional analysis of early replicating DNA in normal human fibroblasts

Stephanie M Cohen, Terrence S Furey, Norman A Doggett, David G Kaufman
2006 BMC Genomics  
The replication of mammalian genomic DNA during the S phase is a highly coordinated process that occurs in a programmed manner.  ...  This was accomplished by first creating a cosmid library containing DNA enriched in sequences that replicate early in the S phase of normal human fibroblasts.  ...  S phase [56] .  ... 
doi:10.1186/1471-2164-7-301 pmid:17134498 pmcid:PMC1702361 fatcat:i4jqkvy7jraqlh3n46ladth7ky

DNaseI hypersensitivity at gene-poor, FSH dystrophy-linked 4q35.2

Xueqing Xu, Koji Tsumagari, Janet Sowden, Rabi Tawil, Alan P. Boyle, Lingyun Song, Terrence S. Furey, Gregory E. Crawford, Melanie Ehrlich
2009 Nucleic Acids Research  
Quantitative real-time polymerase chain reaction (qRT-PCR) was performed (SYBR Green Detection; iQ5, BioRad) with the following parameters: 95 C, 30 s; 63 C, 30 s; 72 C, 30 s for 45 cycles.  ... 
doi:10.1093/nar/gkp833 pmid:19820107 pmcid:PMC2794184 fatcat:aukwq6r4tjhtfkearho3zjjxqe

High-Resolution Mapping and Characterization of Open Chromatin across the Genome

Alan P. Boyle, Sean Davis, Hennady P. Shulha, Paul Meltzer, Elliott H. Margulies, Zhiping Weng, Terrence S. Furey, Gregory E. Crawford
2008 Cell  
Mapping DNase I hypersensitive (HS) sites is an accurate method of identifying the location of genetic regulatory elements, including promoters, enhancers, silencers, insulators, and locus control regions. We employed high-throughput sequencing and wholegenome tiled array strategies to identify DNase I HS sites within human primary CD4 + T cells. Combining these two technologies, we have created a comprehensive and accurate genome-wide open chromatin map. Surprisingly, only 16%-21% of the
more » ... fied 94,925 DNase I HS sites are found in promoters or first exons of known genes, but nearly half of the most open sites are in these regions. In conjunction with expression, motif, and chromatin immunoprecipitation data, we find evidence of cell-type-specific characteristics, including the ability to identify transcription start sites and locations of different chromatin marks utilized in these cells. In addition, and unexpectedly, our analyses have uncovered detailed features of nucleosome structure.
doi:10.1016/j.cell.2007.12.014 pmid:18243105 pmcid:PMC2669738 fatcat:yx6uqb6kirguhksfhaeiubjxk4

Genomic dissection of conserved transcriptional regulation in intestinal epithelial cells

Colin R. Lickwar, J. Gray Camp, Matthew Weiser, Jordan L. Cocchiaro, David M. Kingsley, Terrence S. Furey, Shehzad Z. Sheikh, John F. Rawls, Mary Mullins
2017 PLoS Biology  
Ng AY, Waring P, Ristevski S, Wang C, Wilson T, Pritchard M, et al.  ...  Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, et al.  ... 
doi:10.1371/journal.pbio.2002054 pmid:28850571 pmcid:PMC5574553 fatcat:vujl3m63djam5luytiodesvbwq

Chromatin accessibility reveals insights into androgen receptor activation and transcriptional specificity

Alok K Tewari, Galip Yardimci, Yoichiro Shibata, Nathan C Sheffield, Lingyun Song, Barry S Taylor, Stoyan G Georgiev, Gerhard A Coetzee, Uwe Ohler, Terrence S Furey, Gregory E Crawford, Phillip G Febbo
2012 Genome Biology  
Epigenetic mechanisms such as chromatin accessibility impact transcription factor binding to DNA and transcriptional specificity. The androgen receptor (AR), a master regulator of the male phenotype and prostate cancer pathogenesis, acts primarily through ligand-activated transcription of target genes. Although several determinants of AR transcriptional specificity have been elucidated, our understanding of the interplay between chromatin accessibility and AR function remains incomplete.
more » ... : We used deep sequencing to assess chromatin structure via DNase I hypersensitivity and mRNA abundance, and paired these datasets with three independent AR ChIP-seq datasets. Our analysis revealed qualitative and quantitative differences in chromatin accessibility that corresponded to both AR binding and an enrichment of motifs for potential collaborating factors, one of which was identified as SP1. These quantitative differences were significantly associated with AR-regulated mRNA transcription across the genome. Base-pair resolution of the DNase I cleavage profile revealed three distinct footprinting patterns associated with the AR-DNA interaction, suggesting multiple modes of AR interaction with the genome. Conclusions: In contrast with other DNA-binding factors, AR binding to the genome does not only target regions that are accessible to DNase I cleavage prior to hormone induction. AR binding is invariably associated with an increase in chromatin accessibility and, consequently, changes in gene expression. Furthermore, we present the first in vivo evidence that a significant fraction of AR binds only to half of the full AR DNA motif. These findings indicate a dynamic quantitative relationship between chromatin structure and AR-DNA binding that impacts AR transcriptional specificity.
doi:10.1186/gb-2012-13-10-r88 pmid:23034120 pmcid:PMC3491416 fatcat:zpws77yanbhpbmdumy72unmpuy

A computational screen for site selective A-to-I editing detects novel sites in neuron specific Hu proteins

Mats Ensterö, Örjan Åkerborg, Daniel Lundin, Bei Wang, Terrence S Furey, Marie Öhman, Jens Lagergren
2010 BMC Bioinformatics  
., the conservation score for s depends on the sites in a window of width 21 surrounding s.  ...  is calculated as the negative logarithm of the p-value for the parsimony score in the window centered at s.  ... 
doi:10.1186/1471-2105-11-6 pmid:20047656 pmcid:PMC2831006 fatcat:vwhghst5ijbcndrntj5cyykoea

A Predictive Framework for Integrating Disparate Genomic Data Types Using Sample-Specific Gene Set Enrichment Analysis and Multi-Task Learning

Brian D. Bennett, Qing Xiong, Sayan Mukherjee, Terrence S. Furey, Eric Y. Chuang
2012 PLoS ONE  
We calculated the mean vector m and the covariance matrix S of the genes in the P53PATH-WAY.  ...  We used this to generate baseline expression levels by drawing from a multivariate normal distribution, X 0 ,N(m,S).  ... 
doi:10.1371/journal.pone.0044635 pmid:23028573 pmcid:PMC3441565 fatcat:2x46mbum4fg4zok3rjl5u2zuua
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