Machine Learning can detect the presence of active transcription factors

Jul 09, 2021 | Vanshika Kaushik

Machine Learning can detect the presence of active transcription factors title banner

Transcription factor refers to a protein that controls the rate of transcription in genetic information in DNA and RNA. Transcription factor binds DNA sequence. Some transcription factors stimulate and repress transcription of the related gene. Transcription factors contribute to initiating factors of gene expression. 


It is difficult to identify transcription factors as they get activated only under specific conditions. Scientists at the University of Illinois  have developed a new system that uses a machine learning algorithm and predictive analytics to locate transcription factors inside individual cells. 


The system aims to provide  researchers with an efficient method of identifying the gene regulators. 


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Understanding and manipulating these signals in a cell will be important for biomedical research. . Following the method of signal manipulation within is an effective way that can be used for diagnosing illness. Identification of transcription factors can play an important role in new drug discoveries. 


As reported by Health IT Analytics, Rehman the lead researcher said , "Being able to understand the activity of transcription factors in individual cells would allow researchers to study activity profiles in all the major cell types of major organs such as the heart, brain or lungs."


The machine learning system functions through the combination of new gene expression profile and data gathered from single cell RNA sequencing. 


With all the information, the system  automatically perform multiple computer-based simulations to find the best fit. Further it will predict activity of each anscription factor in the cell. This newly devised approach can be used for the development of regulatory transcription in cells. 


This system will also be applied for predicting the transcription activity in healthy and unhealthy immune systems. 

Tags #Machine learning