155 results found
Maeda N, Kasukawa T, Oyama R, et al., 2006, Transcript annotation in FANTOM3: Mouse gene catalog based on physical cDNAs, PLOS GENETICS, Vol: 2, Pages: 498-503, ISSN: 1553-7404
Andersen M, Lenhard B, Whatling C, et al., 2006, Alternative promoter usage of the membrane glycoprotein CD36, BMC MOLECULAR BIOLOGY, Vol: 7, ISSN: 1471-2199
Ponjavic J, Lenhard B, Kai C, et al., 2006, Transcriptional and structural impact of TATA-initiation site spacing in mammalian core promoters, GENOME BIOLOGY, Vol: 7, ISSN: 1474-760X
Vlieghe D, Sandelin A, De Bleser PJ, et al., 2006, A new generation of JASPAR, the open-access repository for transcription factor binding site profiles, NUCLEIC ACIDS RESEARCH, Vol: 34, Pages: D95-D97, ISSN: 0305-1048
Vlieghe D, Sandelin A, De Bleser PJ, et al., 2006, A new generation of JASPAR, the open-access repository for transcription factor binding site profiles., Nucleic acids research, Vol: 34
JASPAR is the most complete open-access collection of transcription factor binding site (TFBS) matrices. In this new release, JASPAR grows into a meta-database of collections of TFBS models derived by diverse approaches. We present JASPAR CORE--an expanded version of the original, non-redundant collection of annotated, high-quality matrix-based transcription factor binding profiles, JASPAR FAM--a collection of familial TFBS models and JASPAR phyloFACTS--a set of matrices computationally derived from statistically overrepresented, evolutionarily conserved regulatory region motifs from mammalian genomes. JASPAR phyloFACTS serves as a non-redundant extension to JASPAR CORE, enhancing the overall breadth of JASPAR for promoter sequence analysis. The new release of JASPAR is available at http://jaspar.genereg.net.
Carninci P, Kasukawa T, Katayama S, et al., 2005, The transcriptional landscape of the mammalian genome, SCIENCE, Vol: 309, Pages: 1559-1563, ISSN: 0036-8075
Katayama S, Tomaru Y, Kasukawa T, et al., 2005, Antisense transcription in the mammalian transcriptome, SCIENCE, Vol: 309, Pages: 1564-1566, ISSN: 0036-8075
Ståhlberg N, Merino R, Hernández LH, et al., 2005, Exploring hepatic hormone actions using a compilation of gene expression profiles., BMC Physiol, Vol: 5
BACKGROUND: Microarray analysis is attractive within the field of endocrine research because regulation of gene expression is a key mechanism whereby hormones exert their actions. Knowledge discovery and testing of hypothesis based on information-rich expression profiles promise to accelerate discovery of physiologically relevant hormonal mechanisms of action. However, most studies so-far concentrate on the analysis of actions of single hormones and few examples exist that attempt to use compilation of different hormone-regulated expression profiles to gain insight into how hormone act to regulate tissue physiology. This report illustrates how a meta-analysis of multiple transcript profiles obtained from a single tissue, the liver, can be used to evaluate relevant hypothesis and discover novel mechanisms of hormonal action. We have evaluated the differential effects of Growth Hormone (GH) and estrogen in the regulation of hepatic gender differentiated gene expression as well as the involvement of sterol regulatory element-binding proteins (SREBPs) in the hepatic actions of GH and thyroid hormone. RESULTS: Little similarity exists between liver transcript profiles regulated by 17-alpha-ethinylestradiol and those induced by the continuos infusion of bGH. On the other hand, strong correlations were found between both profiles and the female enriched transcript profile. Therefore, estrogens have feminizing effects in male rat liver which are different from those induced by GH. The similarity between bGH and T3 were limited to a small group of genes, most of which are involved in lipogenesis. An in silico promoter analysis of genes rapidly regulated by thyroid hormone predicted the activation of SREBPs by short-term treatment in vivo. It was further demonstrated that proteolytic processing of SREBP1 in the endoplasmic reticulum might contribute to the rapid actions of T3 on these genes. CONCLUSION: This report illustrates how a meta-analysis of multiple transcript profil
Mottagui-Tabar S, Faghihi MA, Mizuno Y, et al., 2005, Identification of functional SNPs in the 5-prime flanking sequences of human genes, BMC GENOMICS, Vol: 6, ISSN: 1471-2164
Pang KC, Stephen S, Engstrom PG, et al., 2005, RNAdb - a comprehensive mammalian noncoding RNA database, NUCLEIC ACIDS RESEARCH, Vol: 33, Pages: D125-D130, ISSN: 0305-1048
Pang KC, Stephen S, Engström PG, et al., 2005, RNAdb--a comprehensive mammalian noncoding RNA database., Nucleic Acids Res, Vol: 33, Pages: D125-D130
In recent years, there have been increasing numbers of transcripts identified that do not encode proteins, many of which are developmentally regulated and appear to have regulatory functions. Here, we describe the construction of a comprehensive mammalian noncoding RNA database (RNAdb) which contains over 800 unique experimentally studied non-coding RNAs (ncRNAs), including many associated with diseases and/or developmental processes. The database is available at http://research.imb.uq.edu.au/RNAdb and is searchable by many criteria. It includes microRNAs and snoRNAs, but not infrastructural RNAs, such as rRNAs and tRNAs, which are catalogued elsewhere. The database also includes over 1100 putative antisense ncRNAs and almost 20,000 putative ncRNAs identified in high-quality murine and human cDNA libraries, with more to be added in the near future. Many of these RNAs are large, and many are spliced, some alternatively. The database will be useful as a foundation for the emerging field of RNomics and the characterization of the roles of ncRNAs in mammalian gene expression and regulation.
Sandelin A, Bailey P, Bruce S, et al., 2004, Arrays of ultraconserved non-coding regions span the loci of key developmental genes in vertebrate genomes, BMC GENOMICS, Vol: 5, ISSN: 1471-2164
Kemmer D, Faxen M, Hodges E, et al., 2004, Exploring the foundation of genomics: a Northern blot reference set for the comparative analysis of transcript profiling technologies, COMPARATIVE AND FUNCTIONAL GENOMICS, Vol: 5, Pages: 584-595, ISSN: 1531-6912
Katzov H, Bennet AM, Kehoe P, et al., 2004, A cladistic model of ACE sequence variation with implications for myocardial infarction, Alzheimer disease and obesity, HUMAN MOLECULAR GENETICS, Vol: 13, Pages: 2647-2657, ISSN: 0964-6906
Sandelin A, Wasserman WW, Lenhard B, 2004, ConSite: web-based prediction of regulatory elements using cross-species comparison, NUCLEIC ACIDS RESEARCH, Vol: 32, Pages: W249-W252, ISSN: 0305-1048
Johansson AM, Katzov H, Lenhard B, et al., 2004, Variants of CYP46A1 interact with age and APOE to influence csf A beta 42 and phospho-tau levels in Alzheimer's disease, 9th International Conference on Alzheimers Disease and Related Disorders, Publisher: ELSEVIER SCIENCE INC, Pages: S505-S505, ISSN: 0197-4580
Alkema WBL, Lenhard B, Wasserman WW, 2004, Regulog analysis: Detection of conserved regulatory networks across bacteria: Application to Staphylococcus aureus, GENOME RESEARCH, Vol: 14, Pages: 1362-1373, ISSN: 1088-9051
Geijer J, Lenhard B, Merino-Martinez R, et al., 2004, Grid computing for the analysis of regulatory elements in CO-regulated sets of genes, Parallel Processing Letters, Vol: 14, Pages: 137-150, ISSN: 0129-6264
We describe an initial implementation of a platform for the analysis of gene promoter architecture for sets of genes from human and other higher organisms, using NorduGrid as the Grid Virtual Organization. The procedure leading from a set of co-regulated genes to a set of inferred common regulatory elements involves a number of computationally intensive, but well scalable steps. We show it is feasible to implement a high performance genomic regulatory sequence analysis pipeline on the Grid with minimal modification to the existing computational biology software components. We applied a job binning step to dramatically reduce the overhead for submitting a set of many small jobs to the Grid. Even with simple jobs and a relatively small size of the Grid, we observed up to 25-fold performance improvement over a comparable or more powerful single or dual-CPU platform, Our implementation of biological sequence alignment and transcription factor binding site algorithms on the Grid proves that even simple applications can take advantage of computational resources that adopted this computational paradigm.
Imanishi T, Itoh T, Suzuki Y, et al., 2004, Integrative annotation of 21,037 human genes validated by full-length cDNA clones, PLOS BIOLOGY, Vol: 2, Pages: 856-875, ISSN: 1545-7885
Johansson A, Katzov H, Zetterberg H, et al., 2004, Variants of CYP46A1 may interact with age and APOE to influence CSF A beta 42 levels in Alzheimer's disease, HUMAN GENETICS, Vol: 114, Pages: 581-587, ISSN: 0340-6717
Fredman D, Munns G, Rios D, et al., 2004, HGVbase: A curated resource describing human DNA variation and phenotype relationships, Nucleic Acids Research, Vol: 32, ISSN: 0305-1048
The Human Genome Variation Database (HGVbase; http://hgvbase.cgb.ki.se) has provided a curated summary of human DNA variation for more than 5 years, thus facilitating research into DNA sequence variation and human phenotypes. The database has undergone many changes and improvements to accommodate increasing volumes and new types of data. The focus of HGVbase has recently shifted towards information on haplotypes and phenotypes, relationships between phenotypes and DNA variation, and collaborative efforts to provide a global resource for genome-phenome data. Open sharing and precise phenotype definitions are necessary to advance the current understanding of common diseases that are typified by complex aetiologies, small genetic effect sizes and multiple confounding factors that obscure positive study results. Association data will increasingly be collected as part of this new project thrust. This report describes the evolving features of HGVbase, and covers in detail the technological choices we have made to enable efficient storage and data mining of increasingly large and complex data sets.
Sandelin A, Alkema W, Engstrom P, et al., 2004, JASPAR: an open-access database for eukaryotic transcription factor binding profiles, NUCLEIC ACIDS RESEARCH, Vol: 32, Pages: D91-D94, ISSN: 0305-1048
Fredman D, Munns G, Rios D, et al., 2004, HGVbase: a curated resource describing human DNA variation and phenotype relationships, NUCLEIC ACIDS RESEARCH, Vol: 32, Pages: D516-D519, ISSN: 0305-1048
Sandelin A, Alkema W, Engström P, et al., 2004, JASPAR: An open-access database for eukaryotic transcription factor binding profiles, Nucleic Acids Research, Vol: 32, ISSN: 0305-1048
The analysis of regulatory regions in genome sequences is strongly based on the detection of potential transcription factor binding sites. The preferred models for representation of transcription factor binding specificity have been termed position-specific scoring matrices. JASPAR is an open-access database of annotated, high-quality, matrix-based transcription factor binding site profiles for multicellular eukaryotes. The profiles were derived exclusively from sets of nucleotide sequences experimentally demonstrated to bind transcription factors. The database is complemented by a web interface for browsing, searching and subset selection, an online sequence analysis utility and a suite of programming tools for genomewide and comparative genomic analysis of regulatory regions. JASPAR is available at http://jaspar.cgb.ki.se.
Sandelin A, Höglund A, Lenhard B, et al., 2003, Integrated analysis of yeast regulatory sequences for biologically linked clusters of genes., Funct Integr Genomics, Vol: 3, Pages: 125-134, ISSN: 1438-793X
Dramatic progress in deciphering the regulatory controls in Saccharomyces cerevisiae has been enabled by the fusion of high-throughput genomics technologies with advanced sequence analysis algorithms. Sets of genes likely to function together and with similar expression profiles have been identified in diverse studies. By fusing an advanced pattern recognition algorithm for identification of transcription factor binding sites with a new method for the quantitative comparison of binding properties of transcription factors, we provide an integrated means to move from expression data to biological insights. The Yeast Regulatory Sequence Analysis system, YRSA, combines standard functions with a novel pattern characterization procedure in an intuitive interface designed for use by a broad range of scientists. The features of the system include automated retrieval of user-defined promoter sequences, binding site discovery by pattern recognition, graphical displays of the observed pattern and positions of similar sequences in the specified genes, and comparison of the new pattern against a collection of binding patterns for characterized transcription factors. The comprehensive YRSA system was used to study the regulatory mechanisms of yeast regulons. Analysis of the regulatory controls of a battery of genes induced by DNA damaging agents supports a putative mediating role for the cell-cycle checkpoint regulatory element MCB. YRSA is available at http://yrsa.cgb.ki.se. [YRSA: ancient Scandinavian name meaning old she-bear (Latin Ursus arctos = brown bear/grizzly).]
Lenhard B, Wahlestedt C, Wasserman WW, 2003, GeneLynx Mouse: Integrated portal to the mouse genome, GENOME RESEARCH, Vol: 13, Pages: 1501-1504, ISSN: 1088-9051
Lenhard B, Sandelin A, Mendoza L, et al., 2003, Identification of conserved regulatory elements by comparative genome analysis., J Biol, Vol: 2
BACKGROUND: For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. RESULTS: We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. CONCLUSIONS: Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.
Okazaki Y, Furuno M, Kasukawa T, et al., 2002, Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs, NATURE, Vol: 420, Pages: 563-573, ISSN: 0028-0836
Lenhard B, Wasserman WW, 2002, TFBS: Computational framework for transcription factor binding site analysis, BIOINFORMATICS, Vol: 18, Pages: 1135-1136, ISSN: 1367-4803
Lenhard B, Hayes WS, Wasserman WW, 2001, GeneLynx: A gene-centric portal to the human genome, GENOME RESEARCH, Vol: 11, Pages: 2151-2157, ISSN: 1088-9051
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