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  • GENE  (10)
  • 1
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    John Wiley & Sons Ltd.
    Keywords: genetics ; gene expression ; EXPRESSION ; microarray ; GENE ; GENE-EXPRESSION
    Type of Publication: Book chapter
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  • 2
    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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  • 3
    Keywords: ENVIRONMENT ; INFORMATION ; GENE ; microarray ; data mining ; SEQUENCE ; SEQUENCES ; polymorphism ; single nucleotide polymorphism ; MICROARRAY DATA ; statistics ; DATABASE ; INTEGRATION ; SINGLE ; GENE-PRODUCT ; SOFTWARE ; ANNOTATION ; RESOURCE ; single-nucleotide ; GENE ONTOLOGY ; ONTOLOGY ; RESOURCES
    Abstract: biomaRt is a new Bioconductor package that integrates BioMart data resources with data analysis software in Bioconductor. It can annotate a wide range of gene or gene product identifiers (e.g. Entrez-Gene and Affymetrix probe identifiers) with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Furthermore biomaRt enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis. Fast and up-to-date data retrieval is possible as the package executes direct SOL queries to the BioMart databases (e.g. Ensembl). The biomaRt package provides a tight integration of large, public or locally installed BioMart databases with data analysis in Bioconductor creating a powerful environment for biological data mining
    Type of Publication: Journal article published
    PubMed ID: 16082012
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  • 4
    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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  • 5
    Keywords: GROWTH ; CELL ; GENE ; GENES ; GENOME ; YEAST ; Drosophila ; CAENORHABDITIS-ELEGANS ; CYCLIN-E ; SCREENS ; SYNTHETIC LETHALITY ; EPISTASIS ; INTERACTION NETWORK
    Abstract: BACKGROUND: Systematic measurement of genetic interactions by combinatorial RNAi (co-RNAi) is a powerful tool for mapping functional modules and discovering components. It also provides insights into the role of epistasis on the way from genotype to phenotype. The interpretation of co-RNAi data requires computational and statistical analysis in order to detect interactions reliably and sensitively. RESULTS: We present a comprehensive approach to the analysis of univariate phenotype measurements, such as cell culture size. The method is based on a quantitative model and is demonstrated on two example Drosophila data sets. We discuss adjustment for technical variability, data quality assessment, model parameter fitting and fit diagnostics, choice of scale, and assessment of statistical significance. CONCLUSIONS: As a result, we obtain quantitative genetic interactions and interaction networks reflecting known biological relationships between the target genes. The reliable extraction of presence, absence, and strength of interactions provides insights into molecular mechanisms.
    Type of Publication: Journal article published
    PubMed ID: 21849035
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  • 6
    Keywords: CANCER ; GROWTH ; INHIBITOR ; proliferation ; SURVIVAL ; tumor ; CELL-PROLIFERATION ; Germany ; KINASE ; INFORMATION ; TOOL ; DISEASE ; GENE ; GENES ; GENOME ; microarray ; PROTEIN ; PROTEINS ; transcription ; TUMORS ; RESOLUTION ; ACTIVATION ; DNA ; BIOLOGY ; cell cycle ; CELL-CYCLE ; CYCLE ; ASSOCIATION ; MOUSE ; IDENTIFICATION ; PROGRESSION ; ASSAY ; microarrays ; PROSTATE-CANCER ; STRATEGIES ; DNA-REPLICATION ; REPLICATION ; signaling ; RE ; TUMORIGENICITY ; genomics ; TRANSITION ; DNA replication ; C-ELEGANS ; cell proliferation ; PROTEIN-ANALYSIS ; development ; ASSAYS ; DIFFERENTIALLY EXPRESSED GENES ; high throughput ; HIGH-THROUGHPUT ; LONG ; PRIME ; PRINCIPLES ; REPRESSOR ; ROLES
    Abstract: Cancer transcription microarray studies commonly deliver long lists of "candidate" genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signal-regulated kinase 1/2 (ERK1/2) signaling (G(1)-S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies
    Type of Publication: Journal article published
    PubMed ID: 16140941
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  • 7
    Keywords: SURVIVAL ; CELL ; Germany ; MICROSCOPY ; screening ; GENE ; GENES ; GENOME ; RNA ; IDENTIFICATION ; ARRAYS ; HUMAN GENOME ; MIGRATION ; PHENOTYPE ; ORGANIZATION ; INTERFERENCE ; RNA INTERFERENCE ; RESOURCE ; SCIENCE ; LIFE ; TISSUE-CULTURE CELLS
    Abstract: Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the similar to 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community
    Type of Publication: Journal article published
    PubMed ID: 20360735
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  • 8
    Keywords: CELLS ; EXPRESSION ; SURVIVAL ; Germany ; IN-VIVO ; PATHWAY ; VIVO ; GENE ; GENE-EXPRESSION ; PROTEIN ; RNA ; transcription ; NF-KAPPA-B ; ACTIVATION ; INFECTION ; TRANSCRIPTION FACTOR ; IMMUNE-RESPONSES ; TARGET ; Drosophila ; MELANOGASTER ; REQUIRES ; HOMOLOG ; IMMUNE-RESPONSE ; FUNCTIONAL GENOMICS ; HOST-DEFENSE ; INTERFERENCE ; RNA INTERFERENCE ; innate immune responses ; IMMUNE ; TOLL ; FUNGAL-INFECTIONS ; Toll signalling
    Abstract: Innate immune signalling pathways are evolutionarily conserved between invertebrates and vertebrates. The analysis of NF-kappa B signalling in Drosophila has contributed important insights into how organisms respond to infection. Nevertheless, significant gaps remain in our understanding of how the activation of intracellular signalling elicits specific transcriptional programs. Here we report a genome-wide RNA interference survey for transcription factors that are required for Toll-dependent immune responses. In addition to the NF-kappa B homologs Dif, Dorsal and factors of the general transcription machinery, we identified Deformed Epidermal Autoregulatory Factor 1 (Deaf1) to be required for the expression of the Toll target gene Drosomycin in cultured cells and in Drosophila in vivo. We show that Deaf1 is required for the survival of flies after fungal, but not E. coli, infection. We determine that Deaf1 acts downstream of the NF-kappa B factors Dorsal and Dif. These results indicate that Deaf1 is an important contributor to innate immune responses in vivo. Copyright (C) 2009 S. Karger AG, Basel
    Type of Publication: Journal article published
    PubMed ID: 20375635
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  • 9
    Keywords: EXPRESSION ; Germany ; GENE ; GENE-EXPRESSION ; microarray ; validation ; gene expression ; MICROARRAY DATA ; microarrays ; DESIGN ; ARRAYS ; NUMBER ; genetics ; affymetrix ; Jun ; VARIANCE ; methods ; Genetic ; RANGE ; DOWNSTREAM ; BACKGROUND CORRECTION ; PROBE LEVEL
    Abstract: Background: Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods. Results: In the present study, 25 different ways of pre-processing Illumina Sentrix BeadChip array data are compared. Among others, methods provided by the BeadStudio software are taken into account. Looking at different statistical measures, we point out the ideal versus the actual observations. Additionally, we compare qRT-PCR measurements of transcripts from different ranges of expression intensities to the respective normalized values of the microarray data. Taking together all different kinds of measures, the ideal method for our dataset is identified. Conclusions: Pre-processing of microarray gene expression experiments has been shown to influence further downstream analysis to a great extent and thus has to be carefully chosen based on the design of the experiment. This study provides a recommendation for deciding which normalization method is best suited for a particular experimental setup
    Type of Publication: Journal article published
    PubMed ID: 20525181
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  • 10
    Keywords: CANCER ; CELLS ; EXPRESSION ; SURVIVAL ; tumor ; TUMOR-CELLS ; carcinoma ; Germany ; PATHWAY ; PATHWAYS ; CLASSIFICATION ; DIAGNOSIS ; CDNA ; GENE ; GENE-EXPRESSION ; GENES ; HYBRIDIZATION ; microarray ; TISSUE ; TUMORS ; PATIENT ; kidney ; GROWTH-FACTOR RECEPTOR ; SEQUENCE ; IDENTIFICATION ; PROGRESSION ; MALIGNANCIES ; PATTERNS ; gene expression ; microarrays ; METASTASIS ; ABNORMALITIES ; C-MYC ; MICROARRAY ANALYSIS ; CDNA MICROARRAYS ; CDNA MICROARRAY ; RENAL-CELL CARCINOMA ; molecular ; MALIGNANCY ; RE ; PATIENT SURVIVAL ; SOLID TUMORS ; EXPRESSED SEQUENCE TAGS ; PROTOONCOGENE ; cytogenetic ; CELL-CARCINOMA ; EXPRESSION PATTERNS ; SIGNATURE
    Abstract: Current diagnosis of renal cancer consists of histopathologic examination of tissue sections and classification into tumor stages and grades of malignancy. Until recently, molecular differences between tumor types were largely unknown. To examine such differences, we did gene expression measurements of 112 renal cell carcinoma and normal kidney samples on renal cell carcinoma-specific cDNA microarrays containing 4,207 genes and expressed sequence tags. The gene expression patterns showed deregulation of complete biological pathways in the tumors. Many of the molecular changes corresponded well to the histopathologic tumor types, and a set of 80 genes was sufficient to classify tumors with a very low error rate. Distinct gene expression signatures were associated with chromosomal abnormalities of tumor cells, metastasis. formation, and patient survival. The data highlight the benefit of microarrays to detect novel tumor classes and to identify genes that are associated with patient variables and tumor properties
    Type of Publication: Journal article published
    PubMed ID: 15701852
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