Detecting Global Inuence of Transcription Factor Interactions on Gene Expression in Lymphoblastoid Cells Using Neural Network Models. Neel Patel Case Western Reserve University https://orcid.org/0000-0001-9953-6734 William S. Bush (
[email protected] ) Case Western Reserve University https://orcid.org/0000-0002-9729-6519 Research Keywords: Transcription factors, Gene expression, Machine learning, Neural network, Chromatin-looping, Regulatory module, Multi-omics. Posted Date: August 3rd, 2021 DOI: https://doi.org/10.21203/rs.3.rs-406028/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models. Neel Patel1,2 and William S. Bush2* 1Department of Nutrition, Case Western Reserve University, Cleveland, OH, USA. 2Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.*-corresponding author(email:
[email protected]) Abstract Background Transcription factor(TF) interactions are known to regulate gene expression in eukaryotes via TF regulatory modules(TRMs). Such interactions can be formed due to co-localizing TFs binding proximally to each other in the DNA sequence or between distally binding TFs via long distance chromatin looping. While the former type of interaction has been characterized extensively, long distance TF interactions are still largely understudied. Furthermore, most prior approaches have focused on characterizing physical TF interactions without accounting for their effects on gene expression regulation. Understanding how TRMs influence gene expression regulation could aid in identifying diseases caused by disruptions to these mechanisms. In this paper, we present a novel neural network based approach to detect TRM in the GM12878 immortalized lymphoblastoid cell line.