000099341 001__ 99341
000099341 005__ 20230914083318.0
000099341 0247_ $$2doi$$a10.1016/j.csbj.2019.09.009
000099341 0248_ $$2sideral$$a122900
000099341 037__ $$aART-2019-122900
000099341 041__ $$aeng
000099341 100__ $$aSantana-Garcia, W.
000099341 245__ $$aRSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
000099341 260__ $$c2019
000099341 5060_ $$aAccess copy available to the general public$$fUnrestricted
000099341 5203_ $$aGene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in Genome-Wide Association Study (GWAS) studies. In this study, we describe improved versions of the programs Variation-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Variation-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted transcription factor affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Variation-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis.
000099341 536__ $$9info:eu-repo/grantAgreement/ES/DGA/A08-17R
000099341 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000099341 590__ $$a6.018$$b2019
000099341 591__ $$aBIOCHEMISTRY & MOLECULAR BIOLOGY$$b43 / 296 = 0.145$$c2019$$dQ1$$eT1
000099341 592__ $$a1.782$$b2019
000099341 593__ $$aBiochemistry$$c2019$$dQ1
000099341 593__ $$aBiophysics$$c2019$$dQ1
000099341 593__ $$aBiotechnology$$c2019$$dQ1
000099341 593__ $$aComputer Science Applications$$c2019$$dQ1
000099341 593__ $$aGenetics$$c2019$$dQ1
000099341 593__ $$aStructural Biology$$c2019$$dQ2
000099341 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000099341 700__ $$aRocha-Acevedo, M.
000099341 700__ $$aRamirez-Navarro, L.
000099341 700__ $$aMbouamboua, Y.
000099341 700__ $$aThieffry, D.
000099341 700__ $$aThomas-Chollier, M.
000099341 700__ $$0(orcid)0000-0002-5462-907X$$aContreras-Moreira, B.$$uUniversidad de Zaragoza
000099341 700__ $$avan Helden, J.
000099341 700__ $$aMedina-Rivera, A.
000099341 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000099341 773__ $$g17 (2019), 1415-1428$$pComput. struct. biotechnol. j.$$tComputational and Structural Biotechnology Journal$$x2001-0370
000099341 8564_ $$s353159$$uhttps://zaguan.unizar.es/record/99341/files/texto_completo.pdf$$yVersión publicada
000099341 8564_ $$s2511949$$uhttps://zaguan.unizar.es/record/99341/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000099341 909CO $$ooai:zaguan.unizar.es:99341$$particulos$$pdriver
000099341 951__ $$a2023-09-13-11:02:05
000099341 980__ $$aARTICLE