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Olga V. Kel-Margoulis

Bio: Olga V. Kel-Margoulis is an academic researcher from Russian Academy of Sciences. The author has contributed to research in topics: Promoter & TRANSFAC. The author has an hindex of 22, co-authored 39 publications receiving 6795 citations.

Papers
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Journal ArticleDOI
TL;DR: 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.

2,262 citations

Journal ArticleDOI
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.
Abstract: 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. Structured fields for expression patterns have been introduced for transcription factors from human and mouse, using the CYTOMER database on anatomical structures and developmental stages. The functionality of Match, a tool for matrix-based search of transcription factor binding sites, has been enhanced. For instance, the program now comes along with a number of tissue-(or state-)specific profiles and new profiles can be created and modified with Match Profiler. The GENE table was extended and gained in importance, containing amongst others links to LocusLink, RefSeq and OMIM now. Further, (direct) links between factor and target gene on one hand and between gene and encoded factor on the other hand were introduced. The TRANSFAC public release is available at http://www.gene-regulation.com. For yeast an additional release including the latest data was made available separately as TRANSFAC Saccharomyces Module (TSM) at http://transfac.gbf.de. For CYTOMER free download versions are available at http://www.biobase.de:8080/index.html.

2,143 citations

Journal ArticleDOI
TL;DR: MatchTM is a weight matrix-based tool for searching putative transcription factor binding sites in DNA sequences that uses the matrix library collected in TRANSFAC® and therefore provides the possibility to search for a great variety of different transcription factorbinding sites.
Abstract: MatchTM is a weight matrix-based tool for searching putative transcription factor binding sites in DNA sequences. MatchTM is closely interconnected and distributed together with the TRANSFAC® database. In particular, MatchTM uses the matrix library collected in TRANSFAC® and therefore provides the possibility to search for a great variety of different transcription factor binding sites. Several sets of optimised matrix cut-off values are built in the system to provide a variety of search modes of different stringency. The user may construct and save his/her specific user profiles which are selected subsets of matrices including default or user-defined cut-off values. Furthermore a number of tissue-specific profiles are provided that were compiled by the TRANSFAC® team. A public version of the MatchTM tool is available at: http://www.gene-regulation.com/pub/programs.html#match. The same program with a different web interface can be found at http://compel.bionet.nsc.ru/Match/Match.html. An advanced version of the tool called MatchTM Professional is available at http://www.biobase.de.

1,069 citations

Journal ArticleDOI
TL;DR: This work developed a new method for identifying composite substructures in regulatory regions of genes consisting of a binding site for a key transcription factor and additional contextual motifs: potential targets for other transcription factors that may synergistically regulate gene transcription.

186 citations

Journal ArticleDOI
TL;DR: The data suggest that the disturbed expression of mucin genes and the connection to the NFκB pathway may influence the integrity of the intestine and therefore contribute to the pathophysiology of IBD.
Abstract: Loss of intestinal mucosa integrity is an important factor in the pathogenesis of inflammatory bowel disease (IBD). The aim of this study was to characterize expression changes and allelic variants of genes related to intestinal epithelial barrier function in this disease. Therefore, ileal and colonic mucosal biopsies from nonaffected regions of patients with ulcerative colitis (UC) and Crohn’s disease (CD), as well as non-IBD probands, were subjected to Affymetrix DNA-microarray analysis. Real-time reverse transcription polymerase chain reaction was used for verification in larger IBD sample numbers. Disturbed mRNA expression was identified for several mucin genes in both disease groups and tissues. A significant downregulation in the colon was obtained for MUC2 in CD and MUC12 in CD and UC. Expression analysis of all dysregulated mucins in a broad human tissue panel revealed dominant epithelial tissue-specific transcription. In silico analysis of the regulatory regions of these mucins indicated nuclear factor κB (NFκB) binding sites in each promoter. Furthermore, NFκB was overrepresented in mucin promoters and a component of a specific combination of transcription factors (composite module). In vivo stimulation experiments in the adenocarcinoma cell line LS174T showed inducible mucin expression by the cytokines tumor necrosis factor-α and transforming growth factor-β, which could be blocked by NFκB signaling inhibitors. Allelic discrimination screening obtained statistically significant associations for the MUC2–V116M (P = 0.003) polymorphism with CD and for MUC4–A585S (P = 0.025), as well as MUC13–R502S (P = 0.0003) with UC. These data suggest that the disturbed expression of mucin genes and the connection to the NFκB pathway may influence the integrity of the intestine and therefore contribute to the pathophysiology of IBD.

176 citations


Cited by
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TL;DR: MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data, detects peaks, isotope clusters and stable amino acid isotope–labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space and achieves mass accuracy in the p.p.b. range.
Abstract: Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.

12,340 citations

Journal ArticleDOI
TL;DR: In this article, the authors found that conventionalization of adult germ-free C57BL/6 mice with a normal microbiota harvested from the distal intestine (cecum) of conventionally raised animals produces a 60% increase in body fat content and insulin resistance within 14 days despite reduced food intake.
Abstract: New therapeutic targets for noncognitive reductions in energy intake, absorption, or storage are crucial given the worldwide epidemic of obesity. The gut microbial community (microbiota) is essential for processing dietary polysaccharides. We found that conventionalization of adult germ-free (GF) C57BL/6 mice with a normal microbiota harvested from the distal intestine (cecum) of conventionally raised animals produces a 60% increase in body fat content and insulin resistance within 14 days despite reduced food intake. Studies of GF and conventionalized mice revealed that the microbiota promotes absorption of monosaccharides from the gut lumen, with resulting induction of de novo hepatic lipogenesis. Fasting-induced adipocyte factor (Fiaf), a member of the angiopoietin-like family of proteins, is selectively suppressed in the intestinal epithelium of normal mice by conventionalization. Analysis of GF and conventionalized, normal and Fiaf knockout mice established that Fiaf is a circulating lipoprotein lipase inhibitor and that its suppression is essential for the microbiota-induced deposition of triglycerides in adipocytes. Studies of Rag1-/- animals indicate that these host responses do not require mature lymphocytes. Our findings suggest that the gut microbiota is an important environmental factor that affects energy harvest from the diet and energy storage in the host. Data deposition: The sequences reported in this paper have been deposited in the GenBank database (accession nos. AY 667702--AY 668946).

5,221 citations

Journal ArticleDOI
Anshul Kundaje1, Wouter Meuleman2, Wouter Meuleman1, Jason Ernst3, Misha Bilenky4, Angela Yen1, Angela Yen2, Alireza Heravi-Moussavi4, Pouya Kheradpour1, Pouya Kheradpour2, Zhizhuo Zhang2, Zhizhuo Zhang1, Jianrong Wang2, Jianrong Wang1, Michael J. Ziller2, Viren Amin5, John W. Whitaker, Matthew D. Schultz6, Lucas D. Ward1, Lucas D. Ward2, Abhishek Sarkar2, Abhishek Sarkar1, Gerald Quon1, Gerald Quon2, Richard Sandstrom7, Matthew L. Eaton2, Matthew L. Eaton1, Yi-Chieh Wu1, Yi-Chieh Wu2, Andreas R. Pfenning1, Andreas R. Pfenning2, Xinchen Wang2, Xinchen Wang1, Melina Claussnitzer2, Melina Claussnitzer1, Yaping Liu1, Yaping Liu2, Cristian Coarfa5, R. Alan Harris5, Noam Shoresh2, Charles B. Epstein2, Elizabeta Gjoneska1, Elizabeta Gjoneska2, Danny Leung8, Wei Xie8, R. David Hawkins8, Ryan Lister6, Chibo Hong9, Philippe Gascard9, Andrew J. Mungall4, Richard A. Moore4, Eric Chuah4, Angela Tam4, Theresa K. Canfield7, R. Scott Hansen7, Rajinder Kaul7, Peter J. Sabo7, Mukul S. Bansal10, Mukul S. Bansal1, Mukul S. Bansal2, Annaick Carles4, Jesse R. Dixon8, Kai How Farh2, Soheil Feizi2, Soheil Feizi1, Rosa Karlic11, Ah Ram Kim2, Ah Ram Kim1, Ashwinikumar Kulkarni12, Daofeng Li13, Rebecca F. Lowdon13, Ginell Elliott13, Tim R. Mercer14, Shane Neph7, Vitor Onuchic5, Paz Polak15, Paz Polak2, Nisha Rajagopal8, Pradipta R. Ray12, Richard C Sallari1, Richard C Sallari2, Kyle Siebenthall7, Nicholas A Sinnott-Armstrong1, Nicholas A Sinnott-Armstrong2, Michael Stevens13, Robert E. Thurman7, Jie Wu16, Bo Zhang13, Xin Zhou13, Arthur E. Beaudet5, Laurie A. Boyer1, Philip L. De Jager15, Philip L. De Jager2, Peggy J. Farnham17, Susan J. Fisher9, David Haussler18, Steven J.M. Jones4, Steven J.M. Jones19, Wei Li5, Marco A. Marra4, Michael T. McManus9, Shamil R. Sunyaev2, Shamil R. Sunyaev15, James A. Thomson20, Thea D. Tlsty9, Li-Huei Tsai2, Li-Huei Tsai1, Wei Wang, Robert A. Waterland5, Michael Q. Zhang21, Lisa Helbling Chadwick22, Bradley E. Bernstein2, Bradley E. Bernstein6, Bradley E. Bernstein15, Joseph F. Costello9, Joseph R. Ecker11, Martin Hirst4, Alexander Meissner2, Aleksandar Milosavljevic5, Bing Ren8, John A. Stamatoyannopoulos7, Ting Wang13, Manolis Kellis2, Manolis Kellis1 
19 Feb 2015-Nature
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

5,037 citations

01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Journal ArticleDOI
TL;DR: Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists, and can be embedded into any tool that performs gene list analysis.
Abstract: System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr .

4,713 citations