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  • PROTEIN  (32)
  • RE  (15)
  • PROTEOMICS  (13)
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  • 1
    Keywords: PROTEOMICS ; genomic ; methods ; LOCALIZATION
    Type of Publication: Book chapter
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  • 2
    Keywords: genomic ; PROTEOMICS
    Type of Publication: Book chapter
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  • 3
    Keywords: NETWORK ; CDNA ; FUNCTIONAL GENOMICS ; PROTEOMICS ; CDNAS
    Abstract: Among the greatest challenges facing biology today is the exploitation of huge amounts of genomic data, and their conversion into functional information about the proteins encoded. For example, the large-scale cDNA sequencing project of the German cDNA Consortium is providing vast numbers of open reading frames (ORFs) encoding novel proteins of completely unknown function. As a first step towards their characterization we have tagged over 500 of these with the green fluorescent protein (GFP), and examined the subcellular localizations of these fusion proteins in living cells. These data have allowed us to classify the proteins into subcellular groups which determines the next step towards a detailed functional characterization. To make further use of these GFP-tagged constructs, a series of functional assays have been designed and implemented to assess the effect of these novel proteins on processes such as cell growth, cell death, and protein transport. Functional assays with such a large set of molecules is only possible by automation. Therefore, we have developed, and adapted, functional assays for use by robotic liquid handling stations and reading stations. A transport assay allows to identify proteins which localize to distinct organelles of the secretory pathway and have the potential to be new regulators in protein transport, a proliferation assay helps identifying proteins that stimulate or repress mitosis. Further assays to monitor the effects of the proteins in apoptosis and signal transduction pathways are in progress. Integrating the functional information that is generated in the assays with data from expression profiling and further functional genomics and proteomics approaches, will ultimately allow us to identify functional networks of proteins in a morphological context, and will greatly contribute to our understanding of cell function.
    Type of Publication: Journal article published
    PubMed ID: 14649292
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  • 4
    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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  • 5
    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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  • 6
    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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  • 7
    Keywords: PEPTIDE ; EXPRESSION ; Germany ; ALGORITHM ; DISTINCT ; GENOME ; PROTEIN ; ACCURACY ; COMPLEX ; COMPLEXES ; SEQUENCE ; SEQUENCES ; MOUSE ; IDENTIFICATION ; PATTERNS ; Drosophila ; NUMBER ; HUMAN GENOME ; LOCALIZATION ; PROTEOMICS ; PROGRAM ; RE ; INCREASE ; REQUIREMENT ; NUCLEOTIDE-SEQUENCES ; FULL-LENGTH HUMAN ; HUMAN CDNAS ; FIDELITY ; Internet
    Abstract: Background: The identification of patterns in biological sequences is a key challenge in genome analysis and in proteomics. Frequently such patterns are complex and highly variable, especially in protein sequences. They are frequently described using terms of regular expressions (RegEx) because of the user-friendly terminology. Limitations arise for queries with the increasing complexity of patterns and are accompanied by requirements for enhanced capabilities. This is especially true for patterns containing ambiguous characters and positions and/or length ambiguities. Results: We have implemented the 3of5 web application in order to enable complex pattern matching in protein sequences. 3of5 is named after a special use of its main feature, the novel n-of-m pattern type. This feature allows for an extensive specification of variable patterns where the individual elements may vary in their position, order, and content within a defined stretch of sequence. The number of distinct elements can be constrained by operators, and individual characters may be excluded. The n-of-m pattern type can be combined with common regular expression terms and thus also allows for a comprehensive description of complex patterns. 3of5 increases the fidelity of pattern matching and finds ALL possible solutions in protein sequences in cases of length-ambiguous patterns instead of simply reporting the longest or shortest hits. Grouping and combined search for patterns provides a hierarchical arrangement of larger patterns sets. The algorithm is implemented as internet application and freely accessible. The application is available at http://dkfz.de/mga2/3of5/3of5.html. Conclusion: The 3of5 application offers an extended vocabulary for the definition of search patterns and thus allows the user to comprehensively specify and identify peptide patterns with variable elements. The n-of-m pattern type offers an improved accuracy for pattern matching in combination with the ability to find all solutions, without compromising the user friendliness of regular expression terms
    Type of Publication: Journal article published
    PubMed ID: 16542452
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  • 8
    Keywords: CELLS ; human ; DISTINCT ; GENE ; GENES ; PROTEIN ; PROTEINS ; COMPLEX ; DOMAIN ; SEQUENCE ; SEQUENCES ; VARIANTS ; MOUSE ; IDENTIFICATION ; PATTERNS ; PROMOTERS ; HUMAN GENOME ; LOCALIZATION ; KAPPA-B ; DOMAINS ; SUBCELLULAR-LOCALIZATION ; RE ; VARIANT ; LOCUS ; EVENTS ; OPEN READING FRAMES ; function ; SPLICING VARIANTS ; transcriptome ; MAMMALIAN GENOMES ; PRE-MESSENGER-RNA
    Abstract: We report the first genome-wide identification and characterization of alternative splicing in human gene transcripts based on analysis of the full-length cDNAs. Applying both manual and computational analyses for 56 419 completely sequenced and precisely annotated full-length cDNAs selected for the H-Invitational human transcriptome annotation meetings, we identified 6877 alternative splicing genes with 18 297 different alternative splicing variants. A total of 37 670 exons were involved in these alternative splicing events. The encoded protein sequences were affected in 6005 of the 6877 genes. Notably, alternative splicing affected protein motifs in 3015 genes, subcellular localizations in 2982 genes and transmembrane domains in 1348 genes. We also identified interesting patterns of alternative splicing, in which two distinct genes seemed to be bridged, nested or having overlapping protein coding sequences (CDSs) of different reading frames (multiple CDS). In these cases, completely unrelated proteins are encoded by a single locus. Genome-wide annotations of alternative splicing, relying on full-length cDNAs, should lay firm groundwork for exploring in detail the diversification of protein function, which is mediated by the fast expanding universe of alternative splicing variants
    Type of Publication: Journal article published
    PubMed ID: 16914452
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  • 9
    Keywords: RECEPTOR ; EXPRESSION ; INVASION ; CELL ; Germany ; KINASE ; PATHWAY ; PATHWAYS ; TYROSINE KINASE ; SYSTEM ; SYSTEMS ; GENE ; GENES ; GENOME ; PROTEIN ; PROTEINS ; validation ; BIOLOGY ; TARGET ; REQUIRES ; PCR ; SIGNALING PATHWAY ; SIGNALING PATHWAYS ; EPITHELIAL-CELLS ; systems biology ; TARGETS ; OVEREXPRESSION ; real-time PCR ; protein expression ; CROSS-TALK ; CYTOTOXICITY ; signaling ; SINGLE ; ARRAY ; analysis ; EVENTS ; technique ; USA ; quantitative ; SIGNALING NETWORK ; protein arrays ; combinatorial protein knockdown ; reverse-phase protein arrays
    Abstract: The elucidation of cross-talk events between intersecting signaling pathways is one main challenge in biological research. The complexity of protein networks, composed of different pathways, requires novel strategies and techniques to reveal relevant interrelations. Here, we established a combinatorial RNAi strategy for systematic single, double, and triple knockdown, and we measured the residual mRNAs and proteins quantitatively by quantitative real-time PCR and reverse-phase protein arrays, respectively, as a prerequisite for data analysis. Our results show that the parallel knockdown of at least three different genes is feasible while keeping both untargeted silencing and cytotoxicity low. The technique was validated by investigating the interplay of tyrosine kinase receptor ErbB2 and its downstream targets Akt-1 and MEK1 in cell invasion. This experimental approach combines multiple gene knockdown with a subsequent quantitative validation of reduced protein expression and is a major advancement toward the analysis of signaling pathways in systems biology
    Type of Publication: Journal article published
    PubMed ID: 17420474
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  • 10
    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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