Computational Biology & Genomics Core
The Computational Biology & Genomics Core (CBGC) is involved in interdisciplinary research and institute-wide training by collaborating mainly with the laboratories in the NIA IRP, NIH.
The goals of the core are to:
- Carry out genomic, epigenomic, functional genomic (CRISPR screens), transcriptomic, single-cell data analysis and data sharing using NIH data-sharing guidelines;
- Coordinate the activities of data scientists at NIA IRP by maintaining a Biomedical Data Science Network (BDSN);
- Acquire and maintain novel high-throughput instruments and high-performance computer systems to achieve the mission of the NIA;
- Have a fully functional, aging-centered core research program which fosters collaborations mainly within NIA IRP, NIH.
The Computational Biology & Genomics Core (CBGC) provides advice on experimental design and sample preparation, quality control of samples, data analysis, data sharing, and training. Apart from the primary focus on genomic and transcriptomic research, CBGC is highly interested in applying Artificial Intelligence (AI) for image analysis and novel genomic data analysis algorithms. The core utilizes gene expression microarrays, Illumina and Oxford Nanopore sequencers and 10x Genomics single-cell sample preparation instruments to meet the needs of NIA IRP researchers. Moreover, CBGC maintains several high-performance computer systems and is involved in designing and maintaining NIA IRP cloud computing for use by all interested NIA IRP researchers.
CBGC is involved in fostering wide variety of collaborative research and providing training on diverse data science topics beyond the core research areas by maintaining the Biomedical Data Science Network (BDSN) comprising of all the data scientists in the NIA IRP. The BDSN website (internal to NIA IRP, sign-in required) provides description of the expertise available at NIA IRP, Baltimore and their contact information.
Core Research Areas
- Role of microbiome in Aging and age-related diseases (e.g., Alzheimer’s Disease)
- Detection of DNA and RNA base modifications
- Applications of Artificial Intelligence in data analysis
- Functional Genomics (CRISPR) Screens
Team
Chris Coletta, MS, Computer Scientist
Deborah Croteau, PhD, Staff Scientist
Elin Lehrmann, PhD, Scientist
Jinshui Fan, PhD, Biologist
Kwan Wood Gabriel Lam, PhD, Staff Scientist
Nirad Banskota, MS, Computer Scientist
Qiong Meng, PhD, Postdoctoral Fellow
Supriyo De, MD, PhD, Chief
Yongqing Zhang, PhD, Computer Scientist
Publications
Selected Recent Publications:
- Anerillas C, Herman AB, Rossi M, Munk R, Lehrmann E, Martindale JL, Cui CY, Abdelmohsen K, De S, Gorospe M. (2022) Early SRC activation skews cell fate from apoptosis to senescence. Science Advances. 8(14):eabm0756. PMID: 35394839.
2021
- Roy R, Ramamoorthy S, Shapiro BD, Kaileh M, Hernandez D, Sarantopoulou D, Arepalli S, Boller S, Singh A, Bektas A, Kim J, Moore AZ, Tanaka T, McKelvey J, Zukley L, Nguyen C, Wallace T, Dunn C, Wersto R, Wood W, Piao Y, Becker KG, Coletta C, De S, Sen JM, Battle A, Weng NP, Grosschedl R, Ferrucci L, Sen R. (2021) DNA methylation signatures reveal that distinct combinations of transcription factors specify human immune cell epigenetic identity. Immunity. 54(11):2465-2480.e5. PMID: 34706222.
- Cochran KR, Veeraraghavan K, Kundu G, Mazan-Mamczarz K, Coletta C, Thambisetty M, Gorospe M, De S. (2021) Systematic Identification of circRNAs in Alzheimer's Disease. Genes. 12(8):1258. PMID: 34440432.
- Herman AB, Anerillas C, Harris SC, Munk R, Martindale JL, Yang X, Mazan-Mamczarz K, Zhang Y, Heckenbach IJ, Scheibye-Knudsen M, De S, Sen P, Abdelmohsen K, Gorospe M. (2021) Reduction of lamin B receptor levels by miR-340-5p disrupts chromatin, promotes cell senescence and enhances senolysis. Nucleic Acids Research. 49(13):7389-7405. PMID: 34181735.
- Tumasian RA 3rd, Harish A, Kundu G, Yang JH, Ubaida-Mohien C, Gonzalez-Freire M, Kaileh M, Zukley LM, Chia CW, Lyashkov A, Wood WH 3rd, Piao Y, Coletta C, Ding J, Gorospe M, Sen R, De S, Ferrucci L. (2021) Skeletal muscle transcriptome in healthy aging. Nature Communications. 12(1):2014. PMID: 33795677.
- Tsitsipatis D, Grammatikakis I, Driscoll RK, Yang X, Abdelmohsen K, Harris SC, Yang JH, Herman AB, Chang MW, Munk R, Martindale JL, Mazan-Mamczarz K, De S, Lal A, Gorospe M. (2021) AUF1 ligand circPCNX reduces cell proliferation by competing with p21 mRNA to increase p21 production. Nucleic Acids Research. 49(3):1631-1646. PMID: 33444453.