Big Data Training for Cancer Research
Big Data Training for Cancer Research
批准号:
10785775
负责人:
MIN ZHANG
金额:
$10.8万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-09-01 至 2024-08-31
关键词:
2019-nCoVAccelerationAddressAreaBig DataBig Data to KnowledgeBioinformaticsBiologicalBiomedical ResearchCOVID-19Case StudyClinicalClinical DataCommunicationCommunitiesComputersDataData AnalysesData ScienceData ScientistData SetDedicationsDiseaseEducationEducational process of instructingEducational workshopFacultyFundingFunding OpportunitiesGoalsGrowthHybridsImmuneImmunologistImmunologyInstructionKnowledgeLiteratureMachine LearningMalignant NeoplasmsMediatingMetagenomicsMotivationOutcomeParticipantPersonsPhysiciansPlasmaPositioning AttributePostdoctoral FellowQuality ControlResearchResearch PersonnelSamplingScanningScienceScientistSelf DirectionStructureTechniquesTimeTrainingTraining ProgramsTranslatingTranslational ResearchUnited States National Institutes of HealthVisualizationWorkanticancer researchbiobankbiomedical scientistclinical investigationcohortcomputer programcomputer sciencecomputerized toolscoronavirus diseasedata integrationdata to knowledgedata visualizationdata wranglingdesignelectronic health record systemempowermentexperiencegraduate studenthigh throughput technologyinstructorinterestlarge scale dataliteratemicrobiomenovelpandemic diseaseprecision medicineprogramsrecruitself-directed learningskillsstatisticstraining opportunity
中文摘要
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英文摘要
PROJECT SUMMARY
Following the NIH Big Data to Knowledge (BD2K) initiative, we have been continuously funded by NCI to create
a two-week summer training program for cancer researchers who are novices in big data analysis. During the
past seven years, we have successfully organized both in-person and online hands-on training opportunities for
traditionally trained biomedical and cancer researchers. Our current workshop uses applications involving cancer
data to teach valuable data science and bioinformatics approaches. However, we strongly believe that these
data science skills are somewhat general. With this funding opportunity, we are excited to extend our workshop
materials with an additional module utilizing data familiar to infectious and immune-mediated disease (IID)
researchers and relevant approaches such as scripting in R, exploratory analysis, data wrangling, and
visualization of longitudinal data. The proposed supplement is directly responsive to NOT-AI-23-010 and will
enable IID researchers to more confidently explore existing IID data, set up their own analysis plans, and
communicate within research teams.
Our proposed supplement course has three goals: (1) Develop two new IID-related case studies for teaching
purposes, both relevant to IID researchers and a more general audience of biomedical researchers; (2) Create
publicly accessible, reusable online materials for IID and cancer research communities that provide instruction
in exploratory data analysis, data wrangling, quality control, and computer programming; and (3) Add these new
case studies and materials to supplement the currently funded workshop on big cancer data as a new hybrid (in-
person and online) pre-module. Like our original R25 workshop, this course will target graduate students,
postdoctoral trainees, physician-scientists, and biomedical scientists, with strong IID backgrounds yet limited
advanced coursework in statistics, bioinformatics, and computer science.
We plan to offer this new module as an addition to our current course rather than as a separate course. Even a
brief scan of the current literature will provide evidence between cancer, immunology (including COVID), and
microbiome. We expect additional benefits for participants based on interdisciplinary interactions and knowledge
they will obtain through participation in the combined course. Finally, many participants in past courses state that
having dedicated time to interact with faculty and other participants and to explore topics of interest independently
gave them the confidence to ask and answer questions—in essence to be self-directed learners.
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Big Data Training for Cancer Research
-
批准号:10880158
-
项目类别:
-
资助金额:$22.43万
-
财政年份:2023
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Cancer Research
-
批准号:10461971
-
项目类别:
-
资助金额:$23.61万
-
财政年份:2019
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Cancer Research
-
批准号:10019476
-
项目类别:
-
资助金额:$23.87万
-
财政年份:2019
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Cancer Research
-
批准号:9793410
-
项目类别:
-
资助金额:$26.46万
-
财政年份:2019
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Cancer Research
-
批准号:10249256
-
项目类别:
-
资助金额:$23.22万
-
财政年份:2019
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Translational Omics Research
-
批准号:9297305
-
项目类别:
-
资助金额:$15.76万
-
财政年份:2015
-
负责人:MIN ZHANG
-
依托单位:
Big Data Training for Translational Omics Research
-
批准号:9044406
-
项目类别:
-
资助金额:$16.2万
-
财政年份:2015
-
负责人:MIN ZHANG
-
依托单位:
Administrative Supplement to: Big Data Training for Translational Omics Research
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批准号:9243817
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项目类别:
-
资助金额:$14.42万
-
财政年份:2015
-
负责人:MIN ZHANG
-
依托单位:
海外基金