Notice Number: NOT-DK-19-024
Key Dates
Release Date: July 31, 2019
Response Date: October 15, 2019
None
Issued by
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Purpose
The National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) invites interested investigators to provide input on their needs for bioinformatics/computational support to advance R01-based research in Diabetes, Endocrinology and Metabolic Diseases. Through this Request for Information (RFI), the NIDDK seeks information from the scientific community about specific bioinformatics and/or computational support that may be scarce or lacking, and that is needed to advance, translate, and accelerate research into causes and consequences of diabetes and other related endocrine or metabolic diseases. The information obtained will aid the NIDDK in future programming of resources to support the research community in these areas.
Background
Contemporary medical research is increasingly dependent on high-dimensional and high-throughput technologies that generate enormous amounts of complex data. Data-intensive experimental approaches such as Genome Wide Association Studies (GWAS), whole genome sequencing, epigenomic mapping, transcriptomics, proteomics, metabolomics profiling, as well as an array of single-cell analyses are increasingly being applied to address NIDDK-relevant research questions. Large volumes of data and computational resources are also required in modern image analysis and for structural determination of proteins and chemical entities involved in biological systems.
Beyond projects generating new data, NIDDK researchers have already produced many large datasets that may benefit from complex computational secondary analyses. Existing datasets may be integrated and mined to identify biomarkers of disease, to assess multifactorial relationships between cells and tissues, and to examine systems biology concepts in the context of disease etiology. In all of these data-intensive research approaches, modern information systems are essential for ensuring that any datasets produced conform to what are known as “FAIR” principles (Findable, Accessible, Interoperable, and Reproducible; Wilkinson MD et al. Sci Data 2106).
Information Requested
This RFI invites input from scientists to help define community needs for bioinformatics and/or computational support to advance research in Diabetes, Endocrinology and Metabolic Diseases. Suggested feedback may include, but is not limited to, input in the following six areas:
- Frequency of investigator needs for or use of computational or bioinformatics support (e.g., none versus intermittent versus frequent);
- Types of datasets routinely generated or utilized (e.g., omics, single cell datasets, biophysical, imaging, EHR/EMR);
- Nature of current analytical support currently available to your research enterprise (e.g., data management/LIMS, statistical analysis and annotation, integration of multiple data types, machine learning/AI, mathematical modeling);
- Additional analytical needs not currently being met (e.g., data management, statistical analysis and annotation, integration of multiple data types, machine learning/AI, mathematical modeling);
- Availability and ease of access to trained computational staff or collaborators;
- Examples of how NIDDK might assist in addressing any current computational or bioinformatics challenges (e.g., brokering collaborations, expanding training, supporting service cores or consultation services, providing online training, tutorials and discussion forums).
How to Submit a Response
Responses to this RFI will be accepted through October 15, 2019. All comments will be anonymous and must be submitted via email to [email protected].
Responses to this RFI are voluntary. The Government is under no obligation to acknowledge receipt of the information provided and respondents will not receive individualized feedback. This RFI is for planning purposes only and should not be construed as a solicitation or as an obligation on the part of the United States Government. NIH will use the information submitted in response to this RFI at its discretion. NIH does not intend to make any type of award based on responses to this RFI or to pay for either the preparation of information submitted or the United States Government's use of such information.
The information submitted will be analyzed and may be shared internally, appear in reports or be reflected in future solicitations, as appropriate and at the Government's discretion. Proprietary, classified, confidential, or sensitive information should not be included in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s) or other activities. No basis for claims against the U.S. Government shall arise as a result of a response to this request for information or from the Government's use of such information.
Inquiries
Please direct all inquiries to:
Xujing Wang, Ph.D.
National Institute of Diabetes and Digestive and Kidney Diseases/ Division of Diabetes, Endocrinology and Metabolic Diseases
Telephone: 301-451-2862
Email: [email protected]
and Human Services (HHS)
