# Core B: Biostatistics Core

> **NIH NIH U19** · BAYLOR COLLEGE OF MEDICINE · 2021 · $270,206

## Abstract

The overarching goal of the Biostatistics and Informatics Core is to provide statistical, informatic and 
computational support for the Program Project to conduct advanced and large-scale statistical analyses to 
identify and characterize the accuracy of risk factors in predicting and screening lung cancer. The Core faculty 
and other researchers engage in mission-related research motivated by questions and methodological 
challenges that arise from these projects. The members of this Core have extensive expertise and interests 
that unite their activities among Projects. By forming a Biostatistics and Informatics Core that functions across 
projects, we anticipate a more robust and profound level of support for Program research than could be 
achieved if biostatisticians were nested within each project. The Core allows us to pool resources (e.g. 
expertise in statistical genetics, statistical and machine learning) across projects and also draw on the broader 
resources available in multiple participating institutes, such as the Department of Biostatistics at Harvard TH 
Chan School of Public Health and the Department of Biomedical Data Science at Dartmouth University. The 
members of the Core have extensive experience in the development and application of new statistical and 
machine learning methods for the study of genetic susceptibility to cancer risk prediction, and risk assessment. 
They have worked together over years on studies relating to lung cancer development. The Core provides an 
environment for coordinating and planning of research across the program projects and to develop and apply 
state-of-the-art statistical and machine learning methods that meet the needs of this Program Project. To 
support the Program projects, we propose the following aims: (1) To ensure that all Projects are grounded in 
sound biostatistical and informatic principles and use state-of-the-art methods for design and analysis; (2) To 
provide expert advice related to design and analysis in statistical genetics, bioinformatics, and machine 
learning and statistical learning for all Projects; (3) To conduct mission-related statistical methods research by 
developing novel statistical methods to address the quantitative needs of the Program Project; (4) To 
disseminate the proposed statistical methodological developments via expository articles, case studies, and 
web-shared software; (5) To provide education and training for researchers and students by working with the 
Steering Committee and the Program investigators. The Core members will coordinate their work activities and 
effectively support the Program Project by having monthly conference calls and regular email exchanges.

## Key facts

- **NIH application ID:** 10135970
- **Project number:** 5U19CA203654-05
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** XIHONG LIN
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $270,206
- **Award type:** 5
- **Project period:** 2017-08-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10135970

## Citation

> US National Institutes of Health, RePORTER application 10135970, Core B: Biostatistics Core (5U19CA203654-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10135970. Licensed CC0.

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