Integrative Bioinformatics

NIH Pandemic-Era Grants

Pandemic Era Grants

2023

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Principal Investigator: Jian-Liang  Li
Organization: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
Fiscal Year: 2023
Award: $2,970,345
Funding agency: National Institute of Environmental Health Sciences

The Integrative Bioinformatics (IB) Support Group provides expertise in computational analysis and develops bioinformatics tools and resources to empower scientific research programs. Equipped with advanced computational infrastructure, including a comprehensive collection of bioinformatics software, the IB group excels in supporting complex biological data analysis. The group has a wealth of experience in managing and analyzing biological data from diverse types of experiments including, but not limited to, NGS data analysis, single cell analysis, microbiome, metabolomics and proteomics data analysis. The group also plays a crucial role in implementing analytical pipelines, establishing best practices, and developing bioinformatics tools to enhance and facilitate intramural research and discovery.

Facilitating Scientific Research and Discovery: 

The IB group provides comprehensive and collaborative bioinformatics supports to research groups and core facilities, playing a crucial role in facilitating research and scientific discovery. During this reporting period, the IB group has actively worked with 39 research groups and 7 data-generating cores from NIEHS, along with five external research labs from UF, UCSC, JHU, Duke, and NHGRI. These collaborations resulted in 22 publications in which the group members were one of the co-authors, including projects like SARS-COV-2 research. For more details about scientific impacts resulting from our collaborative research, please visit our PubMed collection at https://pubmed.ncbi.nlm.nih.gov/collections/61587586/?sort=pubdate.

Advancing Data Analysis and Research Tools:

The IB group is committed to continuously evaluating and enhancing our data analysis capabilities to meet the evolving scientific demands within our intramural community. During this reporting period, we have made significant progress by establishing two new analytical workflows and approaches that effectively facilitate data analysis. Additionally, we have developed one new SOPs focused on Hi-C data analysis, which is a valuable resource for the broader research community. In close collaboration with other research groups, we are actively working on developing single cell endocrine atlas. Furthermore, we are participating in the long-read RNA-seq genome annotation assessment project (LRGASP) consortium, contributing our expertise to further improve genome annotation efforts utilizing long-read RNA-seq data. The completed list of our development publications could be viewed at https://pubmed.ncbi.nlm.nih.gov/collections/61694443/?sort=pubdate.

Empowering Researchers with Tailored Bioinformatics Training:

The IB group offers comprehensive learning opportunities for scientists at all levels within the institute, with a particular emphasis on nurturing the development of bioinformatics concepts and skill sets among trainees, including post-docs, post-bacs, students, and interns. To achieve this goal, we have curated tutorials and workshops designed to empower trainees with essential bioinformatics knowledge and practical skills. In addition, the IB group has coordinated with the Biostatistics Branch and organized biannual short course series of 8 courses in which trainees were the primary attendees. Moreover, the IB group members actively engage in conducting on-demand trainings for those individuals seeking to acquire advanced skills beyond standard data analysis. These tailored sessions provide a platform for participants to explore cutting-edge bioinformatics methods and tackle complex analytical challenges.

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