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  • 1
    Keywords: EXPRESSION ; Germany ; human ; MODEL ; THERAPY ; DIAGNOSIS ; INFORMATION ; NETWORK ; TOOL ; DISEASE ; GENE ; GENES ; GENOME ; PROTEIN ; PROTEINS ; COMPLEX ; COMPLEXES ; BIOLOGY ; SEQUENCE ; FORM ; IDENTIFICATION ; HEALTH ; DATABASE ; PRODUCT ; bioinformatics ; LOCALIZATION ; WEB ; HUMAN GENES ; FUNCTIONAL GENOMICS ; PROTEOMICS ; PRODUCTS ; databases ; ANNOTATION ; RESOURCE ; PROTEIN-ANALYSIS ; FULL-LENGTH HUMAN ; HUMAN CDNAS
    Abstract: As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy
    Type of Publication: Journal article published
    PubMed ID: 15489336
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  • 2
    Keywords: brain ; CELLS ; EXPRESSION ; Germany ; GENE ; GENES ; GENOME ; PROTEIN ; PROTEINS ; transcription ; TISSUE ; MECHANISM ; mechanisms ; PROMOTER ; NUMBER ; DATABASE ; LOCALIZATION ; B-CELLS ; INVOLVEMENT ; TESTIS ; representational difference analysis ; RE ; VARIANT ; genomics ; regulation ; TRANSLATION ; GENE-REGULATION ; gene regulation ; NUCLEAR-PORE COMPLEX ; OVERLAPPING READING FRAMES ; SIGNAL PEPTIDES
    Abstract: Background: Given the complexity of higher organisms, the number of genes encoded by their genomes is surprisingly small. Tissue specific regulation of expression and splicing are major factors enhancing the number of the encoded products. Commonly these mechanisms are intragenic and affect only one gene. Results: Here we provide evidence that the IL4I1 gene is specifically transcribed from the apparent promoter of the upstream NUP62 gene, and that the first two exons of NUP62 are also contained in the novel IL4I1_2 variant. While expression of IL4I1 driven from its previously described promoter is found mostly in B cells, the expression driven by the NUP62 promoter is restricted to cells in testis (Sertoli cells) and in the brain (e.g., Purkinje cells). Since NUP62 is itself ubiquitously expressed, the IL4I1_2 variant likely derives from cell type specific alternative pre-mRNA processing. Conclusion: Comparative genomics suggest that the promoter upstream of the NUP62 gene originally belonged to the IL4I1 gene and was later acquired by NUP62 via insertion of a retroposon. Since both genes are apparently essential, the promoter had to serve two genes afterwards. Expression of the IL4I1 gene from the "NUP62" promoter and the tissue specific involvement of the pre-mRNA processing machinery to regulate expression of two unrelated proteins indicate a novel mechanism of gene regulation
    Type of Publication: Journal article published
    PubMed ID: 16029492
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  • 3
    Keywords: EXPRESSION ; proliferation ; CELL-PROLIFERATION ; Germany ; INFORMATION ; screening ; GENE ; GENE-EXPRESSION ; GENES ; GENOME ; PROTEIN ; PROTEINS ; gene expression ; ASSAY ; DATABASE ; bioinformatics ; INTERFACE ; PROJECT ; INTEGRATION ; FEATURES ; RE ; cell proliferation ; FULL-LENGTH HUMAN ; HUMAN CDNAS ; ASSAYS ; genomic ; NORTHERN
    Abstract: LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface
    Type of Publication: Journal article published
    PubMed ID: 16381901
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  • 4
    Keywords: EXPRESSION ; Germany ; PATHWAY ; CLASSIFICATION ; GENE ; GENE-EXPRESSION ; GENES ; GENOME ; ACCURACY ; BIOLOGY ; TARGET ; gene expression ; MICROARRAY DATA ; DATABASE ; RE ; databases ; analysis ; methods ; HIGH-THROUGHPUT ; technique ; CANDIDATE ; microbiology ; ENGLAND ; biotechnology ; ONTOLOGIES
    Abstract: Background: High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly used and well established technique to test for the statistically significant over-representation of particular pathways. A shortcoming of this method is however, that most genes that are investigated in the experiments have very sparse functional or pathway annotation and therefore cannot be the target of such an analysis. The approach presented here aims to assign lists of genes with limited annotation to previously described functional gene collections or pathways. This works by comparing InterPro domain signatures of the candidate gene lists with domain signatures of gene sets derived from known classifications, e. g. KEGG pathways. Results: In order to validate our approach, we designed a simulation study. Based on all pathways available in the KEGG database, we create test gene lists by randomly selecting pathway genes, removing these genes from the known pathways and adding variable amounts of noise in the form of genes not annotated to the pathway. We show that we can recover pathway memberships based on the simulated gene lists with high accuracy. We further demonstrate the applicability of our approach on a biological example. Conclusion: Results based on simulation and data analysis show that domain based pathway enrichment analysis is a very sensitive method to test for enrichment of pathways in sparsely annotated lists of genes. An R based software package domainsignatures, to routinely perform this analysis on the results of high-throughput screening, is available via Bioconductor
    Type of Publication: Journal article published
    PubMed ID: 18177498
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  • 5
    Keywords: Germany ; CLASSIFICATION ; INFORMATION ; TOOL ; SITE ; CLONING ; GENOME ; PROTEIN ; PROTEINS ; TIME ; SEQUENCE ; SIGNAL ; VARIANTS ; ASSAY ; DATABASE ; LOCALIZATION ; PREDICTION ; SELECTION ; REJECTION ; SEQUENCE-ANALYSIS ; HUMAN GENES ; FUNCTIONAL GENOMICS ; CDNAS ; FEATURES ; PROGRAM ; RE ; VARIANT ; assembly ; databases ; ANNOTATION ; CPG ISLANDS ; FULL-LENGTH HUMAN ; ASSAYS ; HIGH-THROUGHPUT ; TESTS ; GENOMIC DNA ; genomic ; SIGNALS ; E ; SET ; transcriptome ; POLYADENYLATION
    Abstract: Background: The German cDNA Consortium has been cloning full length cDNAs and continued with their exploitation in protein localization experiments and cellular assays. However, the efficient use of large cDNA resources requires the development of strategies that are capable of a speedy selection of truly useful cDNAs from biological and experimental noise. To this end we have developed a new high-throughput analysis tool, CAFTAN, which simplifies these efforts and thus fills the gap between large-scale cDNA collections and their systematic annotation and application in functional genomics. Results: CAFTAN is built around the mapping of cDNAs to the genome assembly, and the subsequent analysis of their genomic context. It uses sequence features like the presence and type of PolyA signals, inner and flanking repeats, the GC-content, splice site types, etc. All these features are evaluated in individual tests and classify cDNAs according to their sequence quality and likelihood to have been generated from fully processed mRNAs. Additionally, CAFTAN compares the coordinates of mapped cDNAs with the genomic coordinates of reference sets from public available resources ( e. g., VEGA, ENSEMBL). This provides detailed information about overlapping exons and the structural classification of cDNAs with respect to the reference set of splice variants. The evaluation of CAFTAN showed that is able to correctly classify more than 85% of 5950 selected "known protein-coding" VEGA cDNAs as high quality multi-or single-exon. It identified as good 80.6% of the single exon cDNAs and 85% of the multiple exon cDNAs. The program is written in Perl and in a modular way, allowing the adoption of this strategy to other tasks like EST-annotation, or to extend it by adding new classification rules and new organism databases as they become available. We think that it is a very useful program for the annotation and research of unfinished genomes. Conclusion: CAFTAN is a high-throughput sequence analysis tool, which performs a fast and reliable quality prediction of cDNAs. Several thousands of cDNAs can be analyzed in a short time, giving the curator/scientist a first quick overview about the quality and the already existing annotation of a set of cDNAs. It supports the rejection of low quality cDNAs and helps in the selection of likely novel splice variants, and/or completely novel transcripts for new experiments
    Type of Publication: Journal article published
    PubMed ID: 17064411
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  • 6
    Keywords: Germany ; human ; SYSTEM ; CDNA ; GENOME ; PROTEIN ; PROTEINS ; SAMPLE ; SEQUENCES ; DATABASE ; INTERFACE ; WEB ; TRACKING ; HUMAN GENES ; FUNCTIONAL GENOMICS ; PROTEOMICS ; CDNAS ; SUBCELLULAR-LOCALIZATION
    Abstract: We have implemented LIFEdb (http://www.dkfz.de/ LIFEdb) to link information regarding novel human full-length cDNAs generated and sequenced by the German cDNA Consortium with functional information on the encoded proteins produced in functional genomics and proteomics approaches. The database also serves as a sample-tracking system to manage the process from cDNA to experimental read-out and data interpretation. A web interface enables the scientific community to explore and visualize features of the annotated cDNAs and ORFs combined with experimental results, and thus helps to unravel new features of proteins with as yet unknown functions
    Type of Publication: Journal article published
    PubMed ID: 14681468
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  • 7
    Keywords: EXPRESSION ; Germany ; human ; DISEASE ; GENE ; GENE-EXPRESSION ; GENES ; TISSUE ; TISSUES ; LINKAGE ; MOUSE ; IDENTIFICATION ; IN-SITU ; gene expression ; NUMBER ; DATABASE ; REGION ; REGIONS ; LOCALIZATION ; ORGANIZATION ; RE ; EXPRESSION PATTERNS ; MAP ; MENTAL-RETARDATION ; SUBUNIT PROTEIN ; CPG-BINDING PROTEIN-2
    Abstract: Background: Well known for its gene density and the large number of mapped diseases, the human sub-chromosomal region Xq28 has long been a focus of genome research. Over 40 of approximately 300 X-linked diseases map to this region, and systematic mapping, transcript identification, and mutation analysis has led to the identification of causative genes for 26 of these diseases, leaving another 17 diseases mapped to Xq28, where the causative gene is still unknown. To expedite disease gene identification, we have initiated the functional characterisation of all known Xq28 genes. Results: By using a systematic approach, we describe the Xq28 genes by RNA in situ hybridisation and Northern blotting of the mouse orthologs, as well as subcellular localisation and data mining of the human genes. We have developed a relational web-accessible database with comprehensive query options integrating all experimental data. Using this database, we matched gene expression patterns with affected tissues for 16 of the 17 remaining Xq28 linked diseases, where the causative gene is unknown. Conclusion: By using this systematic approach, we have prioritised genes in linkage regions of Xq28-mapped diseases to an amenable number for mutational screens. Our database can be queried by any researcher performing highly specified searches including diseases not listed in OMIM or diseases that might be linked to Xq28 in the future
    Type of Publication: Journal article published
    PubMed ID: 16503986
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  • 8
    Keywords: EXPRESSION ; COMBINATION ; SYSTEM ; SYSTEMS ; GENE ; GENE-EXPRESSION ; GENOME ; microarray ; COMPLEX ; MEMBERS ; EXPERIENCE ; gene expression ; MICROARRAY DATA ; ASSAY ; genetics ; DATABASE ; OUTCOMES ; heredity ; PROTEOMICS ; MANAGEMENT ; genomics ; TECHNOLOGY ; USA ; microbiology ; ENGLAND ; biotechnology ; CONSORTIUM ; UK ; DATA STANDARDS ; MINIMUM INFORMATION
    Abstract: This article summarizes the motivation for, and the proceedings of, the first ISA-TAB workshop held December 6-8, 2007, at the EBI, Cambridge, UK. This exploratory workshop, organized by members of the Microarray Gene Expression Data (MGED) Society's Reporting Structure for Biological Investigations (RSBI) working group, brought together a group of developers of a range of collaborative systems to discuss the use of a common format to address the pressing need of reporting and communicating data and metadata from biological, biomedical, and environmental studies employing combinations of genomics, transcriptomics, proteomics, and metabolomics technologies along with more conventional methodologies. The expertise of the participants comprised database development, data management, and hands-on experience in the development of data communication standards. The workshop's outcomes are set to help formalize the proposed Investigation, Study, Assay (ISA)-TAB tab-delimited format for representing and communicating experimental metadata. This article is part of the special issue of OMICS on the activities of the Genomics Standards Consortium (GSC)
    Type of Publication: Journal article published
    PubMed ID: 18447634
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  • 9
    Keywords: human ; GENE ; GENES ; PROTEINS ; SEQUENCE ; ACID ; ACIDS ; NUCLEIC-ACID ; NUCLEIC-ACIDS ; DATABASE ; PREDICTION ; HUMAN GENES ; RE ; ANNOTATION ; RESOURCE ; GENOMIC DNA
    Abstract: Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, proteinprotein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group.
    Type of Publication: Journal article published
    PubMed ID: 18089548
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  • 10
    Keywords: CELLS ; EXPRESSION ; GROWTH ; CELL ; Germany ; CLASSIFICATION ; DEATH ; CDNA ; CLONING ; GENES ; PROTEIN ; PROTEINS ; DOMAIN ; SEQUENCE ; TRANSPORT ; IDENTIFICATION ; CELL-DEATH ; DATABASE ; FUSION PROTEINS ; LOCALIZATION ; LIVING CELLS ; GREEN FLUORESCENT PROTEIN ; FUNCTIONAL GENOMICS ; PROTEOMICS ; CDNAS ; cellular assay,full-length cDNA,functional genomics,protein expression,proteomics ; SUBCELLULAR-LOCALIZATION
    Abstract: To functionally characterize numerous novel proteins encoded by cDNAs sequenced by the German Consortium, 800 were tagged with green fluorescent protein. The subcellular localizations of the fusion proteins were examined in living cells, enabling their classification in subcellular groups. Their activity in cell growth, cell death, and protein transport was screened in high throughput using robotic liquid handling and reading stations. The resulting information is integrated with functional genomics and proteomics data for further understanding of protein functions in the cellular context. (C) 2003 Academie des sciences. Published by Elsevier SAS. All rights reserved
    Type of Publication: Journal article published
    PubMed ID: 14744107
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