The tenet of this application is that progress in biomedical research is increasingly dependent upon high throughput biotechnological advances (e.g., high throughput """"""""next generation"""""""" DNA sequencing, analysis of genomic data for variants, cross-genome comparisons, statistical simulations, protein folding, imaging, electron microscopic structure determination, molecular dynamics, structural biology, high-throughput drug screening, and proteomics) that are increasingly limited by the inability of the """"""""personal computers"""""""" and small departmental clusters available to Yale investigators to adequately and timely analyze the enormous volume of the resulting data. The inexorable trend toward the use of higher throughput technologies in biomedical research that produce ever more massive data sets has resulted in substantially increasing the use of the Yale Biomedical High Performance Computing (HPC) Center such that its instrumentation can no longer meet the surging demand. While recent biotechnological breakthroughs have brought us to the exciting threshold of systems level biomedical research, to take advantage of these technologies Yale investigators will need access to far more powerful high performance computers than are now within the HPC Center and a commensurate level of technical programming and systems administration support. The requested high performance computing instrumentation would enable the Yale Biomedical HPC Center to meet the ever increasing need for bringing more powerful computers to bear on challenging, yet amenable problems that stand in the way of biomedical research. The strengths of this application include the very diverse and productive investigator user base that would Continue to support the Biomedical HPC Center, the almost 30 years of demonstrated ability of the Keck Laboratory to oversee and continually operate and maintain sophisticated biotechnological instrumentation and to bring it within reach of hundreds of Yale and non-Yale researchers, the extensive infrastructure and expertise that is available to bring the requested instrumentation on-line and to oversee and support its continuous use, the demonstrated success of the Biomedical HPC Center that would house the requested instrumentation, and the careful planning and very firm support of both Yale University and its School of Medicine to ensure that this application represents a coordinated and well conceived institutional response to the challenge of providing the high performance computing needed to continue to drive biomedical research forward.

Public Health Relevance

If this application is funded, the requested High Performance Computing instrumentation would provide biomedical researchers'with sufficient shared computing power to analyze the vast amounts of data that will be collected across the Yale campus by an ever increasing number of laboratories using state-of-the-art high throughput DNA sequencing, proteomics, and other technologies. The results of the proposed research would make a very substantial contribution to biomedical research that would extend to and increase our knowledge of embryonic development, epigenetic, hematopoietic differentiation, inflammation, metastasis, protein elasticity, protein folding;infectious diseases such as HIV and influenza, and non-infectious diseases such as hypertension, cancer, diabetes, renal diseases, asthma, amyloid diseases, coronary artery disease, drug addiction, dyslexia, emphysema, and glaucoma. Job Creation Funding of this application would commit Yale University and its Medical School (see attached support letters) to maintaining three years of employment for one Systems administration staff (annual cost is $125,000) and four Ph.D.-level staff, two each in the Keck Laboratory's HPC and Bioinformatics Resources (annual subsidy is $600,000) for a three year total of $2,175,000. Environmental Impact We believe that electrical use/CPU-hr of computing time is less on the requested HPC instrumentation than it is on the existing instrumentation that would be replaced if this application is funded.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-BST-M (30))
Program Officer
Birken, Steven
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Yale University
Schools of Medicine
New Haven
United States
Zip Code
Gaughran, Stephen J; Quinzin, Maud C; Miller, Joshua M et al. (2018) Theory, practice, and conservation in the age of genomics: The Galápagos giant tortoise as a case study. Evol Appl 11:1084-1093
Yang, Y J Daniel; Allen, Tandra; Abdullahi, Sebiha M et al. (2018) Neural mechanisms of behavioral change in young adults with high-functioning autism receiving virtual reality social cognition training: A pilot study. Autism Res 11:713-725
Bae, Taejeong; Tomasini, Livia; Mariani, Jessica et al. (2018) Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 359:550-555
Morozova, Olga; Cohen, Ted; Crawford, Forrest W (2018) Risk ratios for contagious outcomes. J R Soc Interface 15:
Crawford, Forrest W; Aronow, Peter M; Zeng, Li et al. (2018) Identification of Homophily and Preferential Recruitment in Respondent-Driven Sampling. Am J Epidemiol 187:153-160
Zelenev, Alexei; Li, Jianghong; Mazhnaya, Alyona et al. (2018) Hepatitis C virus treatment as prevention in an extended network of people who inject drugs in the USA: a modelling study. Lancet Infect Dis 18:215-224
Berv, Jacob S; Field, Daniel J (2018) Genomic Signature of an Avian Lilliput Effect across the K-Pg Extinction. Syst Biol 67:1-13
Durham, David P; Fitzpatrick, Meagan C; Ndeffo-Mbah, Martial L et al. (2018) Evaluating Vaccination Strategies for Zika Virus in the Americas. Ann Intern Med 168:621-630
Avey, Stefan; Mohanty, Subhasis; Wilson, Jean et al. (2017) Multiple network-constrained regressions expand insights into influenza vaccination responses. Bioinformatics 33:i208-i216
Nguyen, Kevin A; Syed, Jamil S; Luciano, Randy et al. (2017) Optimizing waiting duration for renal transplants in the setting of renal malignancy: is 2?years too long to wait? Nephrol Dial Transplant 32:1767-1773

Showing the most recent 10 out of 54 publications