Mays Cancer Center at UT Health SA

UT Health SA 梅斯癌症中心

• 批准号: 10460433
• 负责人: Yidong Chen
• 金额: $ 26.82万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10460433
• 关键词: Adopted; Adoption; Area; Basic Science; Bioinformatics; Bioinformatics Shared Resource; Biometry; Cancer Center; Cancer Etiology; Catchment Area; Cells; Child; Clinical; Clinical Data; Clinical Research; Clinical Trials; Clinical Trials Database; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Collection; Complex; Conduct Clinical Trials; Data; Data Analyses; Data Collection; Data Science; Data Sources; Data Storage and Retrieval; Development; Doctor of Medicine; Doctor of Philosophy; Education; Ensure; Evaluation; Experimental Designs; Faculty; Fostering; Funding; Genetic; Genomics; Goals; Health; High Performance Computing; High-Throughput Nucleotide Sequencing; Individual; Information Services; Information Systems; Infrastructure; Investigation; Location; Malignant Neoplasms; Manuscripts; Mentorship; Methods; Monitor; Online Systems; Outcome; Peer Review; Performance; Phenotype; Pilot Projects; Population Research; Population Study; Preparation; Procedures; Process; Production; Productivity; Proteomics; Protocols documentation; Publications; Quality Control; Reporting; Research; Research Design; Research Institute; Research Personnel; Research Project Grants; Research Support; Resource Sharing; Resources; Safety; Services; Statistical Data Interpretation; System; Techniques; Testing; Texas; Training; Training and Education; Translational Research; Treatment outcome; Universities; Work; analytical method; analytical tool; anticancer research; base; bioinformatics resource; biomedical data science; cancer health disparity; clinical application; cohort; computing resources; cost efficient; data de-identification; data management; data resource; data sharing; design; experience; experimental study; faculty support; flexibility; genomic data; genomic tools; improved; innovation; instrument; medical schools; member; molecular diagnostics; next generation sequencing; novel; novel therapeutics; operation; programs; protocol development; screening; square foot; survival outcome; tool; tool development; translational applications; translational genomics; treatment trial

Project Summary—Biostatistics and Bioinformatics Shared Resource 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.

生物统计学与生物信息学共享资源 生物统计学和生物信息学共享资源（BBSR）的目的是提供生物统计学和 生物信息学资源的Mays癌症中心（MCC）在得克萨斯州健康圣安东尼奥大学（UT Health SA）。BBSR由拥有高性能计算资源的教职员工沿着组成， 自2001年以来一直在运作的基因组和生物统计数据资源。 整合的生物统计和生物信息学支持和专业知识;用于设计的最先进的数据科学工具 基础、临床和基于人群的研究的发展;以及以数据为重点的教育和培训， 管理协委会成员和受训人员。BBSR由MCC管理。它实际上位于三个地点 包括3，669平方英尺位于Long School of Medicine（LSOM）校园的行政大楼内，占地1，321平方英尺。 在MCC大楼，和2,000平方英尺。Greehey儿童癌症研究所（GCCRI）有 共有五名支持教师和三名工作人员。BBSR与Next保持着密切的关系- 用于研究/实验设计以及数据整合的世代测序共享资源（NGSSR） 从临床和基于人群的研究调查与高通量数据源。陈一东， 博士(PSP)是BBSR的主任，联合主任是Jonathan Gelfond，M.D.，博士（美东时间）。这 集中的核心提供灵活、开放、负责、具有成本效益的生物统计和生物信息学访问 服务必不可少的基础，转化，临床和人口为基础的研究在所有三个程序 的MCC。BBSR强调支持新的研究调查。支助服务以 一致的方式来响应个别研究人员的需求，同时优化我们的共享资源的使用。 整个癌症中心的生物统计学和生物信息学资源。提供的服务包括： 方案制定;统计和生物信息学研究/实验设计和规划;生物信息学和 统计分析;统计监测;和业绩评价。BBSR已经共同撰写了64个癌症- 上一个报告所述期间的相关出版物。2018年，BBSR与30个MCC成员合作， 同行评审的癌症相关资金，占用户总数的45%。预计BBSR的使用量将随着 扩展蛋白质组分析和高通量测序和筛选技术。新文书 用于单细胞数据分析的NGSSR，在MSSR中采用与数据无关的采集方法， 更多使用CRISPR合并筛选技术的MCC成员将提供新的合作机会 共享资源。生物统计服务的使用预计也将每年增加约5% 根据2014-2018年的请求和提供的新服务。