# Boolean Analysis on RT-PCR data

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2023 · $225,000

## Abstract

Project Summary/Abstract
Colon crypt stem cells are characterized by their ability to self-renew, or divide and produce more stem cells, as
well as their ability to differentiate into various specialized cell types, such as absorptive cells, goblet cells, and
enteroendocrine cells, that make up the colon lining. Abnormalities in colon crypt stem cells can lead to the
development of many human gastrointestinal diseases. We have a new method that can predict differentiation
hierarchy using unbiased systems biology perspective and mathematical models of large patient-derived gene
expression datasets. We have mathematical models that can predict the terminally differentiated cells. The
mathematical principle we use is based on Boolean implication logic that has not been commonly applied to
study tissue cell populations. The Boolean analysis assigns a parameter (e.g. RNA level of a gene) with only two
values, i.e., high/low , 1/0, or positive/negative. The primary goal of this proposal is to use Boolean implication
relationships to decode the tissue organization of human colon. Based on our preliminary data the overall
hypothesis is that Boolean principles can be used to specifically characterize the population of cell types in
human colon tissue. In this proposal we are requesting availability of funds for a single equipment purchase of
Bio-Rad CFX Opus Real-time PCR System that will significantly improve gene expression analysis for validation.
These studies are expected to yield information about cell differentiation, diagnostic and prognostic biomarkers.
Consequently, they have the potential to impact current guidelines about how to treat and manage human
diseases and even help identify potential future therapeutic targets.

## Key facts

- **NIH application ID:** 10799309
- **Project number:** 3R01GM138385-04S2
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Debashis Sahoo
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $225,000
- **Award type:** 3
- **Project period:** 2020-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10799309

## Citation

> US National Institutes of Health, RePORTER application 10799309, Boolean Analysis on RT-PCR data (3R01GM138385-04S2). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10799309. Licensed CC0.

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