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JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles

Anthony Mathelier, Xiaobei Zhao, Allen W. Zhang, François Parcy, Rebecca Worsley-Hunt, David J. Arenillas, Sorana Buchman, Chih-yu Chen, Alice Chou, Hans Ienasescu, Jonathan Lim, Casper Shyr (+5 others)
2013 Nucleic Acids Research  
They also thank Michiel de Hoon for the help in the development of the jaspar package as part of BioPython. FUNDING  ...  EXTENSIVE EXPANSION AND IMPROVEMENT OF JASPAR CORE The JASPAR CORE database has been substantially expanded.  ...  Table 1 . 1 Summary of content and growth of the JASPAR CORE database Subset Number of non-redundant profiles in JASPAR 4.0 New non-redundant profiles in JASPAR 5.0 Updated profiles Removed  ... 
doi:10.1093/nar/gkt997 pmid:24194598 pmcid:PMC3965086 fatcat:23dpfm5chjdslg2my5nma6v6hi

JASPAR RESTful API: accessing JASPAR data from any programming language [article]

Aziz Khan, Anthony Mathelier
2017 bioRxiv   pre-print
JASPAR is a widely used open-access database of curated, non-redundant transcription factor binding profiles.  ...  Further, it provides an endpoint to infer the TF binding profile(s) likely bound by a given DNA binding domain protein sequence.  ...  Acknowledgements We thank all JASPAR collaborators for their useful suggestions and testing the API, and Georgios Magklaras for IT support.  ... 
doi:10.1101/160184 fatcat:u46ntu3olrfu7bcllo7m6fyrge

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles

Anthony Mathelier, Oriol Fornes, David J. Arenillas, Chih-yu Chen, Grégoire Denay, Jessica Lee, Wenqiang Shi, Casper Shyr, Ge Tan, Rebecca Worsley-Hunt, Allen W. Zhang, François Parcy (+3 others)
2015 Nucleic Acids Research  
JASPAR ( is an openaccess database storing curated, non-redundant transcription factor (TF) binding profiles represent- ing transcription factor binding preferences as position  ...  Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles.  ...  Weirauch and Mihai Albu for sharing the TF profile inference code implemented in the CIS-BP website, and Roberto Solano and José Manuel Franco-Zorrilla for providing their PBM data.  ... 
doi:10.1093/nar/gkv1176 pmid:26531826 pmcid:PMC4702842 fatcat:dfyf2xpuprh4pg2udndeovgxrm

TFClass: a classification of human transcription factors and their rodent orthologs

Edgar Wingender, Torsten Schoeps, Martin Haubrock, Jürgen Dönitz
2014 Nucleic Acids Research  
TFClass aims at classifying eukaryotic transcription factors (TFs) according to their DNA-binding domains (DBDs).  ...  Predicted TF binding sites from human gene upstream sequences are now also attached to each human TF whenever a PWM was available for this factor or one of his paralogs.  ...  ACKNOWLEDGEMENTS The authors wish to thank Volker Matys and Mathias Krull (BIOBASE GmbH) for their support.  ... 
doi:10.1093/nar/gku1064 pmid:25361979 pmcid:PMC4383905 fatcat:yheg7falpjcrxpsgwyszqfeajq

Machine learning for profile prediction in genomics

Jacob Schreiber, Ritambhara Singh
2021 Current Opinion in Chemical Biology  
In this review, we give an overview of the research works performing profile prediction, define two broad categories of profile prediction tasks, and discuss the types of scientific questions that can  ...  , for example, histone modification, chromatin accessibility, or protein binding.  ...  Noble, Jill Moore, Alex Tseng, Kelly Cochran, and Surag Nair for providing valuable feedback. The figure in the paper is created using  ... 
doi:10.1016/j.cbpa.2021.04.008 pmid:34107341 fatcat:x5sjjif2gjcwzmkzk6wl26cdja

Deciphering regulation in eukaryotic cell: from sequence to function [article]

Valentina Boeva
2014 arXiv   pre-print
Here I describe my contribution to the development of methodology for the discovery of transcription factor binding sites and the positioning of histone proteins.  ...  As two examples, I provide the results of my study of transcriptional regulation by (i) oncogenic protein EWS-FLI1 in Ewing sarcoma and (ii) oncogenic transcription factor Spi-1/PU.1 in erythroleukemia  ...  .  JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles (Mathelier et al. 2014 ).  SwissRegulon: a database of genome-wide annotations of regulatory  ... 
arXiv:1409.6661v1 fatcat:k6n7yfh6sng6lpl2y6zyayhpgu

Which genetic variants in DNase I sensitive regions are functional? [article]

Gregory A Moyerbrailean, Chris T Harvey, Cynthia A Kalita, Xiaoquan Wen, Francesca Luca, Roger Pique-Regi
2014 bioRxiv   pre-print
Here, we present a novel analysis integrating sequence and DNase I footprinting data for 653 samples to predict the impact of a sequence change on transcription factor binding for a panel of 1,372 motifs  ...  Finally, integration of the annotations into 18 GWAS meta-studies improves identification of likely causal SNPs and transcription factors relevant for complex traits.  ...  We would like to thank Joe Pickrell for his assistance in running fgwas and in providing the GWAS meta-analysis datasets, Jacob Degner for reviewing an earlier version of this manuscript, and the members  ... 
doi:10.1101/007559 fatcat:x3zc4qnrcnekvjyhlwqcdjx4da

Prioritizing causal disease genes using unbiased genomic features

Rahul C Deo, Gabriel Musso, Murat Tasan, Paul Tang, Annie Poon, Christiana Yuan, Janine F Felix, Ramachandran S Vasan, Rameen Beroukhim, Teresa De Marco, Pui-Yan Kwok, Calum A MacRae (+1 others)
2014 Genome Biology  
Acknowledgements The work was funded by NIH awards K08 HL098361 (RCD), DP2 OD017483 (RCD), U01 HL107440-03 (RCD and FPR), and by an NIH/NHGRI Center of Excellence in Genomic Science (CEGS) grant (P50 HG004233  ...  FPR was also supported by NIH/NHGRI grant HG001715, an Ontario Research Fund?  ...  Transcription factor binding sites Evolutionarily conserved transcription factor binding sites A list of predicted TFBSs based on evolutionary conservation was downloaded from the ECRbase (Database of  ... 
doi:10.1186/s13059-014-0534-8 pmid:25633252 pmcid:PMC4279789 fatcat:vaxligtsdzfblev632wcjq4nbq

Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data

Michal Dabrowski, Norbert Dojer, Izabella Krystkowiak, Bozena Kaminska, Bartek Wilczynski
2015 BMC Bioinformatics  
Results: We focus on the task of identifying potential transcription factor binding sites in the human genome.  ...  For many years now, binding preferences of Transcription Factors have been described by so called motifs, usually mathematically defined by position weight matrices or similar models, for the purpose of  ...  These include: HOCOMOCO [14] , SwissRegulon [15] and HT-SELEX [13] . The Jaspar database has recently been expanded and updated [16] .  ... 
doi:10.1186/s12859-015-0573-5 pmid:25927199 pmcid:PMC4436866 fatcat:n2hy6c5smrf3ldmzvjmam6zqbu

Targeting the Non-Coding Genome for the Diagnosis of Disorders of Sex Development

Gabby Atlas, Rajini Sreenivasan, Andrew Sinclair
2021 Sexual Development  
We will review the available online tools and databases that can be used to refine regions with potential enhancer activity based on chromosomal accessibility, histone modifications, transcription factor  ...  binding site analysis, chromatin conformation, and disease association.  ...  Conflict of Interest Statement The authors have no conflicts of interest to declare. Funding Sources  ... 
doi:10.1159/000519238 pmid:34634785 fatcat:pdmgcllzi5fx7lypjnstcfhjca

Occupancy maps of 208 chromatin-associated proteins in one human cell type

E. Christopher Partridge, Surya B. Chhetri, Jeremy W. Prokop, Ryne C. Ramaker, Camden S. Jansen, Say-Tar Goh, Mark Mackiewicz, Kimberly M. Newberry, Laurel A. Brandsmeier, Sarah K. Meadows, C. Luke Messer, Andrew A. Hardigan (+8 others)
2020 Nature  
We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP  ...  Transcription factors are DNA-binding proteins that have key roles in gene regulation1,2.  ...  Software Software listed above, described in the methods section of the manuscript, and on the ENCODE portal.  ... 
doi:10.1038/s41586-020-2023-4 pmid:32728244 fatcat:vhzfnqjerrerfjcp72rmp6chxq

The identification of DNA binding regions of the σ54 factor using artificial neural network [article]

Lucas M Ferreira, Roberto T Raittz, Jeroniza N Marchaukoski, Vinicius A Weiss, Izabella C R Santos-Wiess, Paulo A B Costa, Ricardo Voyceik, Liu U Rigo
2018 bioRxiv   pre-print
A single essential σ promotes transcription of thousands of genes and many alternative σ factors promote transcription of multiple specialized genes required for coping with stress or development.  ...  Bacterial genomes have two families of sigma factors, sigma 70 (σ70) and sigma 54 (σ54). σ54 uses a more complex mechanism with specialized enhancers-binding proteins and DNA melting and is well known  ...  JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles.  ... 
doi:10.1101/393736 fatcat:d6ge3hvsjzcrxftg4vxyw3n5yu

Quantification of Differential Transcription Factor Activity and Multiomics-Based Classification into Activators and Repressors: diffTF

Ivan Berest, Christian Arnold, Armando Reyes-Palomares, Giovanni Palla, Kasper Dindler Rasmussen, Holly Giles, Peter-Martin Bruch, Wolfgang Huber, Sascha Dietrich, Kristian Helin, Judith B. Zaugg
2019 Cell Reports  
Transcription factors (TFs) regulate many cellular processes and can therefore serve as readouts of the signaling and regulatory state.  ...  In basic mode, it combines genome-wide chromatin accessibility/activity with putative TF binding sites that, in classification mode, are integrated with RNA-seq.  ...  JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 44 (D1), D110-D115.  ... 
doi:10.1016/j.celrep.2019.10.106 pmid:31801079 fatcat:mtaqoeen7feidcvphnctmm5spq

Motif signatures in stretch enhancers are enriched for disease-associated genetic variants

Daniel X Quang, Michael R Erdos, Stephen C J Parker, Francis S Collins
2015 Epigenetics & Chromatin  
Transcription factors (TFs) can bind to enhancers to modulate enhancer activity, and their sequence specificity can be represented by motifs.  ...  Conclusions: These results reinforce the role of SEs in influencing risk for diseases and suggest an expanded regulatory functional role for motifs that occur outside highly accessible chromatin.  ...  TOMTOM output HTML files documenting the comparison of the discovered motifs to known motifs and CentriMo output text files detailing the enrichment of the discovered motifs in SE or TE DHS sequences are  ... 
doi:10.1186/s13072-015-0015-7 pmid:26180553 pmcid:PMC4502539 fatcat:k2pg2pncibgmdb7d52nwqyt5l4

Gateways to the FANTOM5 promoter level mammalian expression atlas

Marina Lizio, Jayson Harshbarger, Hisashi Shimoji, Jessica Severin, Takeya Kasukawa, Serkan Sahin, Imad Abugessaisa, Shiro Fukuda, Fumi Hori, Sachi Ishikawa-Kato, Christopher J Mungall, Erik Arner (+29 others)
2015 Genome Biology  
This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across  ...  Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.  ...  We would like to thank all members of the FANTOM5 consortium for contributing to generation of samples and analysis of the data-set and thank GeNAS for data production.  ... 
doi:10.1186/s13059-014-0560-6 pmid:25723102 pmcid:PMC4310165 fatcat:7p63sfdvszgc7oetvsyomnr2v4
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