# Core B Computational Modeling and Analysis

> **NIH NIH P01** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2024 · $207,675

## Abstract

ABSTRACT: CORE B -- COMPUTATIONAL MODELING & ANALYSIS (Core Leader: Lauffenburger)
A key premise underlying the motivation for this program is that there exist multiple molecular and cellular
features, in both host and pathogen, that operate integratively via complex cross-talks and feedbacks to govern
TB disease outcomes. This premise is distinct from univariate perspectives that seek individual features
predictive of disease state, and from traditional multivariate perspectives that while admitting effects of numerous
features assume that they operate independently. An associated premise is that heterogeneity is crucial to
comprehend in both animal and human studies. These considerations compel computational analysis and
modeling approaches prioritizing incorporation of multiple features, represented by disparate data types, acting
in coordinated manner and exhibiting different quantitative contributions under disparate circumstances and in
diverse subpopulations. The Computational Modeling & Analysis Core (CMAC) will apply a spectrum of state-of-
art methods, including a number of machine learning techniques, to help address the questions posed in the
Projects, in close partnership with the Project investigators.
Activity 1. Curation, quality control, and feature identification from RNAseq measurements
· Bulk RNAseq from mammalian tissue and blood
· Single-cell RNAseq from mammalian lung and blood cells
· Barcode and genotype identification for I-Mac library from mouse strains
· RNAseq from Mtb strains
Activity 2. Modeling relationships between host immune response properties and Mtb infection outcomes
· Correlation methods
· Unsupervised modeling methods
· Supervised modeling methods
· Cross-species translation modeling methods
Activity 3. Modeling relationships between Mtb genotype, state, and infection outcomes
· Correlation methods
· Unsupervised modeling methods
· Supervised modeling methods
· Network modeling methods

## Key facts

- **NIH application ID:** 10861327
- **Project number:** 1P01AI181898-01
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** DOUGLAS A LAUFFENBURGER
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $207,675
- **Award type:** 1
- **Project period:** 2024-08-20 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10861327

## Citation

> US National Institutes of Health, RePORTER application 10861327, Core B Computational Modeling and Analysis (1P01AI181898-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10861327. Licensed CC0.

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