Our genomics-based scientists and their external collaborators are at a critical point in their research: now, and increasingly over the next years, their discoveries will be limited by the quantity and quality of computing and storage that they can access. While Mount Sinai has funded an excellent supercomputing and storage infrastructure along with professional staff to operate and maintain it, it has been a runaway success and it is now under-provisioned, negatively impacting its largest group of users the greatest: the genomics-based researchers. The scientific productivity of these researchers is greatly inhibited on this existing infrastructure due to long queue wait times especially during critical periods compounded by the extraordinary amount of time spent managing their data storage due to a substantial under-supply. With the explosion of progressively complex scientific and data queries planned by the 20 PIs, their 24 projects and their 55 external collaborating institutions comprising over $43 million in NIH funding, these limited resources are severely restricting the ability of the researchers to collaborate and to share their data with the broader scientific community. To enable these researchers instead to flourish, we propose a """"""""Big Omics Data Engine"""""""" (BODE) instrument: a dedicated, specialized data analytic supercomputer customized for Mount Sinai's specific scientific needs. Such an instrument will increase their throughput by at least 3X and up to 10X by using 2,484 Intel Haswell enterprise cores. The available storage space will expand by over 3X to 5 petabytes, thus greatly enhancing the genomics-based research in a spectrum of disease categories including autism, insulin resistance in diabetics, schizophrenia and related behavioral disorders, cardiac care, the origins of drug addiction and depression, and cancer progression. Moving the genomics researchers to a new machine will also have the secondary effect of freeing up compute cycles and storage on our existing supercomputer for our next highest demand group of users: the structural and chemical biology researchers. In recognition of the intense scientific need for this instrument, Mount Sinai has agreed to fund up to $4 million in operating costs.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
1S10OD018522-01
Application #
8734830
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Klosek, Malgorzata
Project Start
2014-07-03
Project End
2015-07-02
Budget Start
2014-07-03
Budget End
2015-07-02
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Genetics
Type
Schools of Medicine
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10029
Strub, Thomas; Ghiraldini, Flavia G; Carcamo, Saul et al. (2018) SIRT6 haploinsufficiency induces BRAFV600E melanoma cell resistance to MAPK inhibitors via IGF signalling. Nat Commun 9:3440
Galatioto, Josephine; Caescu, Cristina I; Hansen, Jens et al. (2018) Cell Type-Specific Contributions of the Angiotensin II Type 1a Receptor to Aorta Homeostasis and Aneurysmal Disease-Brief Report. Arterioscler Thromb Vasc Biol 38:588-591
LaganĂ , A; Perumal, D; Melnekoff, D et al. (2018) Integrative network analysis identifies novel drivers of pathogenesis and progression in newly diagnosed multiple myeloma. Leukemia 32:120-130
Hong, Jaeyoung; Hatchell, Kathryn E; Bradfield, Jonathan P et al. (2018) Transethnic Evaluation Identifies Low-Frequency Loci Associated With 25-Hydroxyvitamin D Concentrations. J Clin Endocrinol Metab 103:1380-1392
Zhong, Gongxun; Le, Mai Quynh; Lopes, Tiago J S et al. (2018) Mutations in the PA Protein of Avian H5N1 Influenza Viruses Affect Polymerase Activity and Mouse Virulence. J Virol 92:
Nielsen, Jonas B; Fritsche, Lars G; Zhou, Wei et al. (2018) Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development. Am J Hum Genet 102:103-115
Gong, J; Nishimura, K K; Fernandez-Rhodes, L et al. (2018) Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI. Int J Obes (Lond) 42:384-390
Turcot, Valérie (see original citation for additional authors) (2018) Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet 50:26-41
Pandey, Gaurav; Pandey, Om P; Rogers, Angela J et al. (2018) A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data. Sci Rep 8:8826
Linde, Nina; Casanova-Acebes, Maria; Sosa, Maria Soledad et al. (2018) Macrophages orchestrate breast cancer early dissemination and metastasis. Nat Commun 9:21

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