Benjamin Soibam

Associate Professor, University of Houston Downtown

Dr. Soibam's overall research area is computational genomics and applied machine learning with focus on integrative analysis of large scale genomic datasets to decipher regulatory pathways in cellular functions and diseases. Since arriving at UHD, he has established a vibrant research program that involves undergraduate students and graduate students. He has published several peer-reviewed journal papers in journals such as Proceedings of National Acedemy of Sciences, RNA, Nature Scientific Reports, RNA Biology, RNA Biology, Nucleic Acids Research.

In recent years, Dr. Soibam has focused my work on establishing functional links between long noncoding RNAs and genome organization. The goal is to investigate and validate the role of such long noncoding RNAs in mediating genome organization by integrating large scale datasets from different sequencing platforms as Hi-C, ChIP-Seq, RNA-Seq, and DBD-Seq. He has years of experience in analyzing, integrating, and interpreting large scale genome sequencing data.


  • Computational Biology
  • Machine Learning
  • Data Science
  • Bioinformatics