# Computational Core

> **NIH NIH P01** · BETH ISRAEL DEACONESS MEDICAL CENTER · 2024 · $237,701

## Abstract

Computational Analysis Core (Core C) - Project Summary
The primary objective of the Computational Analysis Core (Core C) is to provide centralized statistical and
bioinformatics services for, and collaboration on, the research projects of this P01. Core C will serve as the focal
point for P01 investigators to draw statistical and bioinformatics expertise for the design and analysis of their
research projects as well as for staffing support to execute the planned studies. Core C will enable a deep, multi-
model understanding to help identify cellular and/or spatial signatures that can predict or inform mechanisms of
interventional efficacy against HIV viral reservoirs. The Specific Aims of the Core are to: 1) use established
computational methods to power, quality control, and analyze bulk/single-cell genomics data; 2) use established
computational methods to quality control and analyze spatial-omics data; and 3) Cross-platform and -species
integration of single-cell and spatial-omics data for identifying predictive features of HIV interventional efficacy.
Core C members will be involved in all Projects at every research stage. As the Projects yield results, the Core
will conduct data analyses, prepare any necessary reports, and assist investigators with the preparation of
presentations and manuscripts. Core C will be co-led by Drs. Qin Ma (Ohio State University), Sizun Jiang
(Harvard Medical School), Alex K. Shalek (MIT/Ragon Institute/Broad Institute), and Dongjun Chung (Ohio
State University). All Core members have extensive experience in applied biostatistics and bioinformatics
methods for serology, bulk, single-cell, and spatial multi-omics data. They will work closely with other cores (e.g.,
Multi-omics Core) for seamless integration of all aspects of this innovative P01 project. Specifically, Drs. Ma
and Shalek will oversee bulk and single-cell related data analyses, Drs. Jiang and Ma will oversee spatial omics
data analysis (including CODEX and CosMX), and Dr. Chung will oversee the statistical and power analyses.
Moreover, the integrative analysis of single-cell and spatial-omics data will be collaboratively overseen by all
members. In summary, Core C will ensure rigor and reproducibility by applying accepted and appropriate
statistical and bioinformatics methods to data analysis, by clearly describing methodology, rationale, and
interpretations in reports and manuscripts, and by openly sharing research results and data.

## Key facts

- **NIH application ID:** 10886127
- **Project number:** 5P01AI177687-02
- **Recipient organization:** BETH ISRAEL DEACONESS MEDICAL CENTER
- **Principal Investigator:** Qin Ma
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $237,701
- **Award type:** 5
- **Project period:** 2023-07-11 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10886127

## Citation

> US National Institutes of Health, RePORTER application 10886127, Computational Core (5P01AI177687-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10886127. Licensed CC0.

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