# Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response

arXiv: https://arxiv.org/abs/2301.01769 · HTML: https://mlsanity.com/paper/2301.01769/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 34 references that are in the map.
- First posted on arXiv 3 Jan 2023.

## Built on by (most cited first, 2 of 2)

- [Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge](https://mlsanity.com/paper/2307.08813/) (2023)
- [Density Estimation via Measure Transport: Outlook for Applications in the Biological Sciences](https://mlsanity.com/paper/2309.15366/) (2023)

## Abstract (arXiv)

There are various sources of ionizing radiation exposure, where medical exposure for radiation therapy or diagnosis is the most common human-made source. Understanding how gene expression is modulated after ionizing radiation exposure and investigating the presence of any dose-dependent gene expression patterns have broad implications for health risks from radiotherapy, medical radiation diagnostic procedures, as well as other environmental exposure. In this paper, we perform a comprehensive pathway-based analysis of gene expression profiles in response to low-dose radiation exposure, in order to examine the potential mechanism of gene regulation underlying such responses. To accomplish this goal, we employ a statistical framework to determine whether a specific group of genes belonging to a known pathway display coordinated expression patterns that are modulated in a manner consistent with the radiation level. Findings in our study suggest that there exist complex yet consistent signatures that reflect the molecular response to radiation exposure, which differ between low-dose and high-dose radiation.