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      GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

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          Abstract

          GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3′-UTR GeneChips), genome-wide protein–DNA binding assays and protein–protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions.

          Database URL: www.germonline.org/

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          Most cited references 45

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          RNA-Seq: a revolutionary tool for transcriptomics.

          RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.
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            Transcriptional regulatory code of a eukaryotic genome.

            DNA-binding transcriptional regulators interpret the genome's regulatory code by binding to specific sequences to induce or repress gene expression. Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation, but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeast's transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast's transcriptional regulators.
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              Automated generation of heuristics for biological sequence comparison

              Background Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. We introduce bounded sparse dynamic programming (BSDP) to allow rapid approximation to exhaustive alignment. This is used within a framework whereby the alignment algorithms are described in terms of their underlying model, to allow automated development of efficient heuristic implementations which may be applied to a general set of sequence comparison problems. Results The speed and accuracy of this approach compares favourably with existing methods. Examples of its use in the context of genome annotation are given. Conclusions This system allows rapid implementation of heuristics approximating to many complex alignment models, and has been incorporated into the freely available sequence alignment program, exonerate.
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                Author and article information

                Journal
                Database (Oxford)
                database
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2010
                10 December 2010
                10 December 2010
                : 2010
                Affiliations
                1Inserm, U625, GERHM; IFR-140; Université de Rennes 1; F-35042 Rennes, France, 2School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland and 3Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1; F-35042 Rennes, France
                Author notes
                *Corresponding author: Tel: +33 2 2323 6178; Email: michael.primig@ 123456inserm.fr

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

                Article
                baq030
                10.1093/database/baq030
                3004465
                21149299
                © The Author(s) 2010. Published by Oxford University Press.

                This is Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Pages: 9
                Categories
                Database Update

                Bioinformatics & Computational biology

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