TRANSFAC® and its module TRANSCompel®: transcriptional gene regulation in eukaryotes
V. Matys,Olga V. Kel-Margoulis,Ellen Fricke,Ines Liebich,Sigrid Land,A. Barre-Dirrie,Ingmar Reuter,D. Chekmenev,Mathias Krull,Klaus Hornischer,Nico Voss,Philip Stegmaier,Birgit Lewicki-Potapov,H. Saxel,Alexander E. Kel,Edgar Wingender +15 more
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TLDR
The TRANSFAC® database on transcription factors, their binding sites, nucleotide distribution matrices and regulated genes as well as the complementing database TRANSCompel® on composite elements have been further enhanced on various levels.Abstract:
The TRANSFAC database on transcription factors, their binding sites, nucleotide distribution matrices and regulated genes as well as the complementing database TRANSCompel on composite elements have been further enhanced on various levels. A new web interface with different search options and integrated versions of Match and Patch provides increased functionality for TRANSFAC. The list of databases which are linked to the common GENE table of TRANSFAC and TRANSCompel has been extended by: Ensembl, UniGene, EntrezGene, HumanPSD and TRANSPRO. Standard gene names from HGNC, MGI and RGD, are included for human, mouse and rat genes, respectively. With the help of InterProScan, Pfam, SMART and PROSITE domains are assigned automatically to the protein sequences of the transcription factors. TRANSCompel contains now, in addition to the COMPEL table, a separate table for detailed information on the experimental EVIDENCE on which the composite elements are based. Finally, for TRANSFAC, in respect of data growth, in particular the gain of Drosophila transcription factor binding sites (by courtesy of the Drosophila DNase I footprint database) and of Arabidopsis factors (by courtesy of DATF, Database of Arabidopsis Transcription Factors) has to be stressed. The here described public releases, TRANSFAC 7.0 and TRANSCompel 7.0, are accessible under http://www.gene-regulation.com/pub/databases.html.read more
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IRF2 is a master regulator of human keratinocyte stem cell fate
Nicolas Mercado,Gabi Schutzius,Christian Kolter,David Estoppey,Sebastian Bergling,Guglielmo Roma,Caroline Gubser Keller,Florian Nigsch,Adrian Salathe,Remi Terranova,John S. Reece-Hoyes,John Alford,Carsten Russ,Judith Knehr,Dominic Hoepfner,Alexandra Aebi,Heinz Ruffner,Tanner C. Beck,Sajjeev Jagannathan,Calla M. Olson,Hadley E. Sheppard,Selma Z. Elsarrag,Tewis Bouwmeester,Mathias Frederiksen,Felix Lohmann,Charles Y. Lin,Susan Kirkland +26 more
TL;DR: In this article, the authors investigate whether transcriptional circuitry also governs phenotypic changes within a given cell type by comparing human primary keratinocytes with intrinsically high versus low stem cell potential.
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Epigenetic predisposition to reprogramming fates in somatic cells.
TL;DR: It is found that if one daughter cell contributes to a lineage that generates induced pluripotent stem cells (iPSCs), its paired sibling will as well, suggesting that the potential to reprogram is predetermined within a select subpopulation of cells and heritable, at least over the short term.
Journal ArticleDOI
Anthracyclines induce the accumulation of mutant p53 through E2F1-dependent and -independent mechanisms.
Monika Bug,Matthias Dobbelstein +1 more
TL;DR: It is shown that even closely related anthracyclines induce the synthesis of different, opposing transcripts from the TP53 locus, which suggests a reciprocal activation pattern of TP53 and WRAP53 by different chemotherapeutics.
Journal ArticleDOI
How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene’s Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter
Mikhail P. Ponomarenko,D. A. Rasskazov,Olga Arkova,P. M. Ponomarenko,V. V. Suslov,Ludmila Savinkova,Nikolay A. Kolchanov +6 more
TL;DR: This work used the Web service involving Fisher's Z-score for candidate SNP markers to find a significant change in a gene's expression via a change in affinity of the TATA-binding protein for this promoter.
Journal ArticleDOI
Predicting target DNA sequences of DNA-binding proteins based on unbound structures
TL;DR: The conformational change of proteins upon binding DNA was shown to be the key factor in the first attempt to predict target sequences of DNA-binding proteins from their unbound structures, which sheds light on the challenge of predicting the target DNA sequences of a protein lacking co-crystallized structures.
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TRANSFAC®: transcriptional regulation, from patterns to profiles
V. Matys,Ellen Fricke,Robert Geffers,Ellen Gößling,Martin Haubrock,Reinhard Hehl,Klaus Hornischer,Dagmar Karas,Alexander E. Kel,Olga V. Kel-Margoulis,Dorothee-U. Kloos,Sigrid Land,Birgit Lewicki-Potapov,Holger Michael,Richard Münch,Ingmar Reuter,Stella Rotert,H. Saxel,Maurice Scheer,S. Thiele,Edgar Wingender +20 more
TL;DR: The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data.
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