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TEAM

Predicting cis-regulatory elements using scRNAseq

Gonzalo Morales Chaya, Juan Sebastian Jaramillo, FAN HUANG

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Introduction
Every cell in an organism contains the same DNA, but different cells perform different functions. This happens because specific genes are turned on or off by special proteins called transcription factors (TFs). These proteins help determine whether a cell becomes a muscle cell, a neuron, or any other type of cell. If TFs do not work correctly, it can lead to developmental disorders and diseases. Understanding how TFs regulate gene expression is crucial for studying how cells develop and function.
Project Goal
We aims to develop a tool that predicts how transcription factors regulate gene expression—whether they activate, repress, or work in combination in different cell types using data from single-cell RNA sequencing. This type of data consists of a data frame that contains gene expression across individual cells. Our tool will analyze these patterns using machine learning algorithms to identify transcription factor activity across different cell types

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