Co-Directors: Bruce Stanton, PhD, Andrew C. Vail Professor of Microbiology and Todd MacKenzie, PhD, Professor of Biomedical Data Science
| Staff | Areas of Expertise |
| Todd MacKenzie, Ph.D. | General Statistical Consulting, Clinical Trials, Association Studies, and Predictive Modeling |
| Tom Hampton, Ph.D. | Core Manager, General Statistical Consulting, Bioinformatics, R, Microbiome Analysis, Integrated Omics Analysis, FAIR Data Practices |
| Kiyoshi Fukutani, Ph.D. | R, Gene Regulatory Networks, Complex Data Representation |
| Lily Charpentier | R, Interactive Graphics, Accessing Public Data, Python, RNA-seq |
| Lily Taub | C, R, Python, SQL, Ruby |
Location: The CF-BBC office suite is located in 506 Remsen Building on the Hanover Campus of Dartmouth College.
Description:
The CF-BBC is a shared-use facility providing state-of-the-art, biologically-driven data science expertise to enhance the ability of CF researchers to harness big data following the principles of Open Science. We collaborate across the entire life cycle of projects—from design and interpretation of preliminary experiments, development of hypotheses, and design of high-throughput experiments to iterative interpretation of results, drafting of figures and tables, submission of data to repositories, and manuscript preparation and support for grant applications. The CF-BBC:
- Provides expert-level bioinformatics and biostatistical support to CF scientists at Dartmouth, our collaborating institutions, and peer P30 CF Centers
- Improves the extent to which CF project data are findable, accessible, interoperable, and reusable (FAIR) by CF investigators world-wide. This includes the development and availability of RESPIRE.
- Provides training opportunities to CF and biomedical data scientists that enhance their ability to perform research involving large data sets
Specifically, the CF-BBC can assist with:
- Study design, including power analysis and choice of high throughput platform
- Guidance on choice of statistical tools
- Iterative, biology-driven, bioinformatics analysis of high throughput data including 16S metagenomics, proteomics, mRNA, lncRNA and miRNA
- Drafting of figures and text for CF research manuscripts
- Identification of opportunities for follow up experiments and manuscripts
- Development of subject and sample annotation standards for CF sample data, beginning with 16S metagenomics samples
- Development of a prototype CF data repository for CF metagenomic datasets (CFMDR)
Training: The CF-BBC also provides training and educational opportunities to CF and biomedical data scientists, including:
- Formal courses (Applied Bioinformatics and Microbiome Bioinformatics Workshop)
- Weekly “R Club” seminars
- Annual retreat to enhance the ability to perform collaborative research in CF involving large data sets.
FAIR Bioinformatics Course: Click the link below to access full recordings of the FAIR Bioinformatics Courses.
