[Raise-faculty] Fwd: NIH funding opportunity: Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)

[Vassilis Tsotras]

Dear RAISE faculty,
in case you missed it, please find below info about an NIH funding
opportunity on Bioinformatics and Computational Biology that relates to AI
and ML. Let us know if there is interest.

Deadlines:
June 5, 2026
October 5, 2026
4 years, $1M in direct costs

best,
Vassilis and Amit


---------- Forwarded message ---------
From: Brandon Reese <breese at ucr.edu>
Date: Fri, Feb 13, 2026 at 2:02 PM
Subject: NIH funding opportunity: Advancing Bioinformatics, Translational
Bioinformatics and Computational Biology Research (R01 Clinical Trial
Optional)
To: <csfaculty at cs.ucr.edu>, <eceprofs at ece.ucr.edu>
Cc: Huguette Albrecht <huguetta at ucr.edu>, Aimee Anaya <aanaya at engr.ucr.edu>,
Lucy Matsukawa <lmats003 at engr.ucr.edu>


*NIH: Advancing Bioinformatics, Translational Bioinformatics and
Computational Biology Research (R01 Clinical Trial Optional)*

The National Library of Medicine (NLM) wishes to advance groundbreaking and
innovative research in bioinformatics, translational bioinformatics and
computational biology, which are related areas of biomedical informatics
that aim to understand biological data using storage, analytic and
interpretive methods. This initiative will support NLM's mission to
accelerate discovery by enhancing human health through data-driven research.

This funding opportunity aims to address the growing need to leverage
transformative technologies—such as artificial intelligence (AI), machine
learning, and large-scale computational platforms—to extract actionable
knowledge from vast, diverse, and complex biological datasets. By enabling
more effective interpretation and integration of multi-dimensional
biological and biomedical data, this research will ultimately contribute to
improving individual and population health outcomes.

For this funding opportunity, areas of bioinformatics and computational
biology for which methodological advances are of interest include, but are
not limited to:

·         Various types of omics and multi-omics studies, including
genomics, transcriptomics, proteomics, epigenomics, structural or spatial
omics, comparative omics, and multimodal integrations of those.

·         Microbiome studies, including studies on host-microbiome
interactions.

·         Metagenomic and/or metaproteomic studies.

·         Studies that use artificial intelligence (AI) and machine
learning (ML) applications for predictive and analytical bioinformatics
research.

·         Computational biology method development for analysis of genomic
or non-genomic biological data and related phenomena.

·         Genetic variation and disease association studies, including
methodological advances for determining combinatorial variant associations,
and for accelerating discovery beyond rare diseases, such as for chronic
diseases.

·         Phenotypic studies, including methodological advances for complex
trait analyses.

·         Translational bioinformatic studies that aim to provide a pathway
for effective treatment strategies or have a tangible effect on health
outcomes.

·         Translational bioinformatic studies applicable to personalized or
genomic medicine.

·         Pathway and/or regulatory network studies.

·         Systems biology studies, including analysis and visualization of
large datasets.

·         Cell-cell interaction informatics, and other types of
cellular/tissue/organism networking studies.

·         Single cell informatics.

·         Informatics related to biomarker discovery.

·         Analysis of drug targets.

·         Various emerging or other informatics studies on biological data,
including but not limited to multimodal studies that encompass multiple
data types and/or research domains, or studies relevant to bioinformatic
data harmonization, integration          and reuse.

Example topics of interest include, but are not limited to:

·         Interdisciplinary approaches that are informed by functional
biological and/or biomedical data.

·         Approaches that result in whole usable pipelines, workflows or
resources, rather than software products that perform segmented functions
in a larger workflow.

·         Tools and methods that can be developed, applied, evaluated and
disseminated within the scope of the proposed project, and which are
durable and autonomously updatable.

·         Tools and workflows that are FAIR (Findable, Accessible,
Interoperable, Reusable) and easily findable by the wide research community
in well-documented, user-friendly, publicly available resources, and which
encompass ethical considerations          for data representation and
downstream use.

·         Translational bioinformatics approaches that are broadly
adaptable and generalizable.

·         Non-translational bioinformatics advances that contribute
tangible functional knowledge for downstream use.

·         Computational models that are adaptable, credible, explainable
and testable by real-world data.

*Budget and Project Period: *Up to $250K per year in direct costs over 4
years

*Submission Deadlines: *

·         June 5, 2026

·         October 5, 2026

**Recurring deadlines in 2027 and 2028



*For more information, go to: *
https://www.grants.gov/search-results-detail/359003

*Brandon Reese*

Contract and Grant Facilitator

Bourns College of Engineering

University of California, Riverside

*breese at ucr.edu <breese at ucr.edu>*
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