Computational Methods for Deep Sequencing Based RBP Binding Motif Characterizatio
Computational Methods for Deep Sequencing Based RBP Binding Motif Characterizatio
批准号:
8188156
负责人:
Luiz Otavio Penalva
金额:
$40.51万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-13 至 2014-06-30
关键词:
AlgorithmsApoptosisAreaAttentionBase SequenceBindingBinding SitesBiological AssayBiologyCellsCharacteristicsClassificationCommunitiesComplementComplexComputer AnalysisComputing MethodologiesDataData SetDatabasesDevelopmentDiseaseElementsEukaryotic CellGene ExpressionGene Expression ProfileGene TargetingGenesGenetic TranscriptionGenomicsGoalsHCT116 CellsHumanIndividualLearningLuciferasesMalignant NeoplasmsMapsMediatingMessenger RNAMethodologyMethodsMutagenesisOutcomePatternPlayPositioning AttributeProtein BindingProtein Binding DomainProtein FamilyPsyche structureRNARNA SplicingRNA analysisRNA-Binding ProteinsReadingRegulationResearchResearch PersonnelResourcesRoleSamplingSiteSpecificityStatistical MethodsStatistical ModelsStructureTechniquesTechnologyTimeTranscriptTranscription factor genesTranscriptional RegulationTranslationsValidationVariantbasecolon cancer cell linedata integrationdesignflexibilityhigh throughput technologyimprovedin vivomembermethod developmentmodel developmentpreferencepromoterprotein complexresearch studytask analysistranscription factor
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): RNA binding proteins can have 100s to 1000s of target mRNAs thanks to flexibility in recognizing their binding sites. These sites can incorporate both sequence and structural elements and show tremendous variation when binding motifs of different RBPs are compared, even among members of the same RBP family. Until early 2000s, characterization of binding sites was mostly restricted to individual studies involving a particular RBP and a target gene/binding motif. Only in the last decade, en masse identification of in vivo binding motifs became possible; first with the RIP-chip approach and then with CLIP and RIP-seq. These last two methods incorporate the power of deep sequencing, allowing us not only to identify more binding sites but also to conduct a more refined mapping. One area that urges attention is the development of computational methods to perform comprehensive analyses of datasets generated by these techniques. In this project we will profile targets for five RBPs with RIP-seq in two colon cancer cell lines. We will design and implement a framework for characterizing the binding specificity of RNA binding proteins. We will evaluate and refine methodology for RBP target identification from such data. Finally, we will develop a database of information about RNA-binding proteins, their target genes, binding sites and binding specificities.
PUBLIC HEALTH RELEVANCE: The identification of sequence encoded factors that influence human gene expression is central to our understanding of how gene expression is regulated. Analytical methodology developed in this project will enable researchers to leverage the full potential of cutting-edge and emerging experimental technologies for profiling regulatory activities of RNA binding proteins. Understanding the regulatory functions of RNA binding proteins has implications for our understanding of several diseases, including cancers and developmental diseases.
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