Established in 2015 by the National Institute of Mental Health (NIMH), the PsychENCODE Consortium (PEC) is a multi-site investigation of the genomic basis of neuropsychiatric diseases. The aim is to create a resource of mechanistic insights to guide future therapeutic development.
Genomic influences on neural function are remarkably complex, characterized by a highly polygenic risk architecture and often located in the non-coding parts of the genome. A key objective of PEC is to delineate an enhanced framework of regulatory genomic elements associated with neuropsychiatric disorders.
Multidisciplinary PEC teams are working to generate large-scale gene expression and regulatory data from human postmortem brains across several major psychiatric disorders. Brain tissue is characterized across multiple developmental stages and include bulk tissue, single cell, and sorted cell types. The goal is to map and functionally validate disease‐associated variants, regulatory elements, genes and cell types.
Data from Phase I was presented in a collection of 11 papers published in Science, Science Translational Medicine, and Science Advances. This collection is summarized in the Science special issue “Revealing the brain’s molecular architecture” . Phase II – which will enhance cellular and developmental resolution – is currently underway.
The NIMH has funded the Brain Somatic Mosaicism Network (BSMN) with the goal of accelerating the discovery of somatic genomic variation across human brain cell and tissue types to explain the role of somatic mosaicism in the development of mental illnesses.
Collectively, the BSMN is examining large numbers of neurons and bulk tissue from neurotypic controls alongside matched individuals with Autism Spectrum Disorder, Bipolar Disorder, Focal Cortical Dysplasia, Schizophrenia, and Tourette Syndrome. Data are generated by whole genome and exome sequencing, and other genomic assays. These datasets are being made available to the research community, together with data exploration tools and other resources.
Use this portal to learn about the BSMN research teams and the grant projects supporting their work. Discover tools that may assist your research, and access BSMN generated data managed through the NIMH Data Archive (NDA).
AACR Project GENIE is a publicly accessible international cancer registry of real-world data assembled through data sharing between 19 of the leading cancer centers in the world. Through the efforts of strategic partners Sage Bionetworks and cBioPortal, the registry aggregates, harmonizes, and links clinical-grade, next-generation cancer genomic sequencing data with clinical outcomes obtained during routine medical practice from cancer patients treated at these institutions. The consortium and its activities are driven by openness, transparency, and inclusion, ensuring that the project output remains accessible to the global cancer research community for the benefit of all patients. AACR Project GENIE fulfills an unmet need in oncology by providing the statistical power necessary to improve clinical decision-making, particularly in the case of rare cancers and rare variants in common cancers. Additionally, the registry can power novel clinical and translational research.
As data is collected from nearly every patient sequenced at participating institutions and have committed to sharing only clinical-grade data, the GENIE registry contains enough high-quality data to power decision making on rare cancers or rare variants in common cancers. The GENIE data provides another knowledge turn in the virtuous cycle of research, accelerating the pace of drug discovery, improving the clinical trial design, and ultimately benefiting cancer patients globally.
The dHealth Digital Health Knowledge Portal, a resource to catalyze digital and mobile health research by providing data, analysis tools, and benchmarked outcomes and digital biomarkers.
We make these resources available to the community to help accelerate the field of digital health. Developing validated digital measures, outcomes or biomarkers requires quality data, analytical tools, and benchmarking. Our goal is to enable this process by democratizing access to data, by providing reusable computational tools, and by sharing research best practices.
The dHealth Knowledge Portal is an effort of Sage Bionetworks. We believe that digital tools can help us better understand the real-world environment’s impact on our individual experience of health and disease. Learn more about our digital health programs.
The NCI Division of Cancer Biology supports multiple research programs composed of interdisciplinary communities of scientists who aim to integrate approaches, data, and tools to address important questions in basic and translational cancer research. Discover and download datasets, publications, and other resources generated by these programs.
Cancer Systems Biology Consortium: The CSBC initiative supports research that investigates the challenges of complexity in basic and translational cancer research through the explicit combination of experimental biology and computational modeling, multi-dimensional data analysis, and systems engineering. Visit Website
Physical Sciences in Oncology: This initiative seeks to establish research projects that bring together cancer biologists and oncologists with scientists from the fields of physics, mathematics, chemistry, and engineering to address some of the major questions and barriers in cancer research. Visit Website
The AD Knowledge Portal is a platform for accessing data, analyses, and tools that the National Institute on Aging’s (NIA) Alzheimer’s Disease Translational Research Program generates through several initiatives. The program encourages open-science collaborations that share resources early in the research life cycle.
The AD Knowledge Portal initially hosted data from the Accelerating Medicines Partnership in Alzheimer’s Disease Target Discovery and Preclinical Validation Project. The AD Knowledge Portal now includes “omics” data from human samples and experimental model systems, as well as bioinformatic analyses from research teams and cross-consortium working groups.
The NF Data Portal is designed to help openly explore and share NF datasets, analysis tools, resources, and publications related to neurofibromatosis. Anyone can join the NF Open Science Initiative (NF-OSI) to participate! We welcome contributions from anyone in the neurofibromatosis and schwannomatosis research community, such as original datasets generated by the community or analyses of data from the NF Data Portal.
Neurofibromatosis and Schwannomatosis
Neurofibromatosis (NF) is a group of diseases including neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SCH). These syndromes can afflict patients with a broad range of symptoms including tumors, developmental hardships, and pain. Many of these symptoms have few or no treatment options. Learn more about this family of diseases here .
Agora hosts high-dimensional human transcriptomic, proteomic, and metabolomic evidence for whether or not genes are associated with Alzheimer’s disease (AD). Agora also contains a list of over 600 nascent drug targets for AD that were nominated by AD researchers. The list of nominated targets was contributed by researchers from the National Institute on Aging’s Accelerating Medicines Partnership in Alzheimer’s Disease (AMP-AD) consortium and Target Enablement to Accelerate Therapy Development for Alzheimer’s Disease TREAT-AD centers, as well as other research teams. Other evidence presented in Agora was either generated by AMP-AD and TREAT-AD research teams, or is aggregated from publicly available data sources.
Agora is funded by the National Institute on Aging. It is developed and maintained by Sage Bionetworks.