# Computational resources and systems biological analyses of deep sequencing data for improved

> **NIH NIH P01** · HARVARD MEDICAL SCHOOL · 2020 · $147,474

## Abstract

Core C Project Leader: Wall, Dennis P.
Project Summary / Abstract
The study of miRs and their regulatory control has led to impressive bioinformatic innovations with respect to
algorithm design, target prediction, evolutionary canalization and divergence, and much more. What has not
happened and is unique to this plan is the combination of these informatics advances with comprehensive and
integrated functional analysis in the intact animal. Core C, through its interactions with Core B and the three
driving biological projects targeting regulatory influence of miRs on sleep, associative learning and memory,
and the neuromuscular system will provide this innovation in a model organism where neural circuits can be
analyzed at many levels from behavior to cellular and molecular details. Specifically, Core C will develop the
informatics infrastructure necessary to store and analyze all experimental data coming from these 4 sectors of
the center proposal and, through reciprocal design, enable fast characterization of the functional impacts of
specific miRs to study the impact on target networks and to determine instances of functional convergence.
Core C will deliver the tools necessary for each driving project to form hypotheses about the influence of
specific miRs on gene networks through microRNA recognition elements (MREs) in target mRNAs, and help
steer the design of new experiments that have the highest likelihood of revealing the mechanisms of regulatory
control that impact phenotype.

## Key facts

- **NIH application ID:** 9910459
- **Project number:** 5P01NS090994-05
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Dennis Paul Wall
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $147,474
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9910459

## Citation

> US National Institutes of Health, RePORTER application 9910459, Computational resources and systems biological analyses of deep sequencing data for improved (5P01NS090994-05). Retrieved via AI Analytics 2026-06-10 from https://api.ai-analytics.org/grant/nih/9910459. Licensed CC0.

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