Post-Doctoral Researcher

Research Emphasis

My research is primarily focused on solving complex biological problems using big data analysis approaches. Specifically, I have employed machine learning techniques to analyze transcription data of Pseudomonas aeruginosa to reconstruct transcriptional regulatory networks (TRNs) and address several crucial questions such as the regulation of efflux pumps, reannotation of biosynthetic gene clusters, and the role of iron and sulfur stimulons in growth, among others. Furthermore, I have utilized pangenomic analysis to identify Two-Component Systems (TCSs) as potential drug targets for ESKAPEE pathogens. In addition, I have employed multi-omics data analysis methods to examine the differential response of antibiotics on bacteriological and physiological media types.



I am a highly skilled computational biologist with over 10 years of expertise in a range of areas, including multi-omics data analysis, systems biology, prediction algorithms, cheminformatics, phylogenomics, and the development of databases and webservers. My research has focused on important topics such as antimicrobial resistance, biofilms, bacterial cell-cell communication, and virology. In addition to my computational skills, I also possess hands-on experience in experimental techniques, such as developing biofilms and investigating the effects of inhibitors. Whether working independently or as part of a team, I bring strong communication skills and a proven track record of publications.