grant

Mays Cancer Center at UT Health SA

Organization UNIVERSITY OF TEXAS HLTH SCIENCE CENTERLocation SAN ANTONIO, UNITED STATESPosted 1 Aug 1997Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY20250-11 years oldAccelerationAccountabilityAdoptedAdoptionAreaBasic ResearchBasic ScienceBioinformaticsBioinformatics Shared ResourceBiometricsBiometryBiostatisticsCRISPRCRISPR/Cas systemCancer CauseCancer CenterCancer EtiologyCancersCatchment AreaCell BodyCellsChildChild YouthChildren (0-21)ClinicalClinical DataClinical ResearchClinical StudyClinical TrialsClinical Trials DatabaseClustered Regularly Interspaced Short Palindromic RepeatsCollaborationsCollectionComplexConduct Clinical TrialsDataData AnalysesData AnalysisData CollectionData ScienceData SourcesData Storage and RetrievalData SystemsDevelopmentDoctor of MedicineDoctor of PhilosophyEducationEducation and TrainingEducational aspectsEnsureEvaluationExperimental DesignsFacultyFosteringFundingGeneticGenomic TestingGenomicsGoalsHealthHigh Performance ComputingHigh-Throughput Nucleotide SequencingHigh-Throughput SequencingIT SystemsIndividualInformation ServicesInformation SystemsInformation Technology SystemsInfrastructureInvestigationInvestigatorsLocationM.D.Malignant NeoplasmsMalignant TumorManuscriptsMentorshipMethodsMonitorNGS MethodNGS systemOn-Line SystemsOnline SystemsOutcomePeer ReviewPerformancePh.D.PhDPhenotypePilot ProjectsPopulation ResearchPopulation StudyPopulation-based researchPopulation-level researchPreparationProceduresProcessProductionProductivityProteomicsProtocolProtocols documentationPublicationsQuality ControlR-Series Research ProjectsR01 MechanismR01 ProgramReportingResearchResearch DesignResearch GrantsResearch InstituteResearch PersonnelResearch Project GrantsResearch ProjectsResearch ResourcesResearch SupportResearchersResource SharingResourcesSafetyScientific PublicationServicesStatistical Data AnalysesStatistical Data AnalysisStatistical Data InterpretationStudy TypeSystemTechniquesTexasTrainingTraining and EducationTranslational ResearchTranslational ScienceTreatment outcomeUniversitiesWorkanalytical methodanalytical toolanti-cancer researchbio-informatics resourcebio-informatics shared resourcebioinformatics resourcebiomedical data sciencecancer researchclinical applicabilityclinical applicationcohortcomputational resourcescomputing resourcescost efficientdata de-identificationdata deidentificationdata integrationdata interpretationdata managementdata resourcedata retrievaldata sharingdata storagede-identified datadeidentified datadesigndesigningdevelopmentalexperiencefaculty supportflexibilityflexiblegenome based testinggenome testinggenomic DNA testinggenomic based testinggenomic clinical testinggenomic datagenomic datasetgenomic profiling testinggenomic screening testgenomic toolshigh-end computingimprovedinnovateinnovationinnovativeinstrumentkidsmalignancymedical collegemedical schoolsmembermolecular diagnosticsneoplasm/cancernew drug treatmentsnew drugsnew pharmacological therapeuticnew therapeuticsnew therapynext gen sequencingnext generation sequencingnext generation therapeuticsnextgen sequencingnovelnovel drug treatmentsnovel drugsnovel pharmaco-therapeuticnovel pharmacological therapeuticnovel therapeuticsnovel therapyonline computeroperationoperationspilot studypopulation-based studypopulation-level studypreparationsprogramsprotocol developmentschool of medicinescreeningscreeningssq. ftsquare footstatistical analysisstudies of populationsstudy designstudy of the populationsurvival outcometooltool developmenttranslation researchtranslational applicationstranslational genomicstranslational investigationtreatment trialweb basedyoungster
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Full Description

The purpose of the Biostatistics and Bioinformatics Shared Resource (BBSR) is to provide biostatistics and bioinformatics resources to the Mays Cancer Center (MCC) at the University of Texas Health San Antonio (UT Health SA). The BBSR is comprised of faculty and staff along with high-performance computing resources and genomic and biostatistical data resources that have been in operation since 2001.The BBSR provides consolidated biostatistical and bioinformatics support and expertise; state-of-the-art data science tools for design and development of basic, clinical, and population-based studies; and data-focused education and training to MCC members and trainees. The BBSR is managed by the MCC. It is physically housed in three locations including 3,669 sq.ft. in the Administration Building on the Long School of Medicine (LSOM) campus, 1,321 sq.ft. in the MCC building, and 2,000 sq.ft. in the Greehey Children’s Cancer Research Institute (GCCRI).

There are a total of five supported faculty and three staff members. The BBSR maintains a close relationship with the Next- Generation Sequencing Shared Resource (NGSSR) for study/experimental design as well as integrating data from clinical and population-based research investigations with high-throughput data sources. Yidong Chen, Ph.D. (PSP) is the Director of the BBSR and the co-Director is Jonathan Gelfond, M.D., Ph.D. (EDT). This centralized core provides flexible, open accountable, cost-efficient access to biostatistics and bioinformatics services essential to the basic, translational, clinical and population-based research across all three programs of the MCC.

The BBSR emphasizes support of new research investigations. Support services are provided in a consistent manner to be responsive to the needs of individual researchers while optimizing the use of our shared biostatistical and bioinformatics resources across the entire Cancer Center. Services that are provided include: protocol development; statistical and bioinformatics study/experiment design and planning; bioinformatics and statistical analysis; statistical monitoring; and performance evaluation. The BBSR has co-authored 64 cancer- related publications during the last reporting period.

In 2018, the BBSR worked with 30 MCC members with peer-reviewed cancer-related funding, 45% of the total number of users. BBSR usage is anticipated to grow with expanding proteomic profiling and high-throughput sequencing and screening techniques. New instruments in the NGSSR for single-cell data analysis, adoption of data-independent acquisition methods in the MSSR, and more MCC members using CRISPR pooled screening techniques will offer new opportunities to collaborate across the Shared Resources. Use of biostatistical services is also expected to increase by about 5% per year based on requests from 2014-2018 and new services offered.

Grant Number: 3P30CA054174-29S1
NIH Institute/Center: NIH

Principal Investigator: Yidong Chen

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