Feng Cheng, Associate Professor
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Associate Editor
Term Expiration:
12/31/2024
Affiliation(s):
College of Pharmacy; University of South Florida
ORCID URL:
Areas of Interest:
bioinformatics
Biography & Research:
I have related expertise and appropriate training in bioinformatics, biostatistics, computational biology, and pharmaceutical science. I have published more than 70 papers in these research fields. These papers have been cited over 3,400 times. In bioinformatics and biostatistics, I focused on RNA sequencing and microbiome data analysis. In addition, I identified reliable genetic biomarkers from microarray and the RNAseq data for drug efficacy or toxicity prediction and disease diagnosis. For example, I have identified 56 gene biomarkers from monocytes to predict early-stage atherosclerosis using a machine learning approach. This work was published on BMC Med Genomics and has been rated as a “Highly accessed paper” of the journal. This achievement was reported internationally by news services including YAHOO, Brazil News, and HongKong News. I also successfully developed a new hepatoxicity prediction model that has been patented in the USA. In addition, I participated in the “Brainspan Consortium” which conducted a comprehensive study on the spatiotemporal human brain transcriptome using exon microarray technique and gene pathway analysis. This project has generated one paper published in Nature, of which I am a co-first author. I have also developed two important online web servers, TIBS (Transcriptome of Irritable Bowel Syndrome) and SEGEL (Smoking Effects on Gene Expression of Lungs). These two online servers are useful tools and resources that biologists without a bioinformatics background can use to investigate the effects of Irritable Bowel Syndrome and cigarette smoking on gene expression changes. In pharmaceutical science, we developed a novel algorithm for analyzing drug-drug interactions from MEDLINE literature and FDA FAERS database. I have identified the molecular mechanism of several important drug/compounds including artemisinin, rosiglitazone, phosphonates, bisphosphonates, diphosphates, and orlistat using computational chemistry methods.
