R24 - White 1R24MH114788-01

A BRAIN Initiative resource: The neuroscience multi-omic data archive

The Neuroscience Multi-Omic (NeMo) Archive is a data repository specifically focused on the storage and dissemination of omic data generated from the BRAIN Initiative and related brain research projects. Containing knowledge from varied sources in one resource allows traversal between datatypes based on common metadata. The information incorporated into the NeMO archive enables, in part, understanding of 

  • Genomic regions associated with brain abnormalities and disease;  
  • Transcription factor binding sites and other regulatory elements;  
  • Transcription activity;  
  • Levels of cytosine modification;  
  • Histone modification profiles and chromatin accessibility.  

This resource allows users to answer diverse questions of relevance to brain research, such as identifying diagnostic candidates, predicting prognosis, selecting treatments, and testing hypotheses. It also provides the basic knowledge to guide the development and execution of predictive and machine learning algorithms in the future. The NeMO Archive is consistent with the principles advanced by the NIH Strategic Plan for Data Science, including FAIR Principles, documentation of APIs, data-indexing systems, workflow sharing, use of shareable software pipelines and storage on cloud-based systems. 

Project Leadership

Owen White, Ph.D. (Principal Investigator) 
Professor, Epidemiology and Public Health 
University of Maryland School of Medicine 
Associate Director, Institute for Genome Sciences 


Seth Ament, Ph.D. (Co-investigator) 
Assistant Professor, Department of Psychiatry 
University of Maryland School of Medicine  


Michelle Giglio, Ph.D. (Co-investigator) 
Associate Professor, Medicine 
University of Maryland School of Medicine 
Associate Director, Analysis, Institute for Genome Sciences 


Anup Mahurkar (Co-investigator) 
Executive Director, Bioinformatics Software Engineering, 
Institute for Genome Sciences 


Lynn Schriml, Ph.D. (Co-investigator) 
Associate Professor, Epidemiology and Public Health,  
University of Maryland School of Medicine 

Project Data Types

  • Single cell transcriptomic and epigenetic data.

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