Dr. Mahmoud ElHefnawi has been the biomedical informatics and chemoinformatics group leader since 2009 and is a professor at the Informatics and Systems Department at National Research Centre. He was also a part-time adjunct associate professor and senior scientist at Nile University as well as adjunct faculty in many other universities. He has led many projects in bioinformatics, gene therapy, cancer, and drug discovery as well as machine learning and artificial intelligence in biomedicine. He is also the PI for many projects including an affiliated node for the H3 bionet NIH African project. He has published international publications on topics including rational drug design; docking; gene therapy using siRNA and miRNA for infectious diseases and cancer; structural bioinformatics and motif predictions applications in virology; applications of machine learning in bioinformatics and medical informatics; as well as other bioinformatics and medical biotechnology applications. His interests span the computational biology field as well as the medical biotechnology and life sciences fields. From the informatics and engineering point, he has used data mining and classification algorithms, deep learning models, HMM models, motif prediction algorithms, and other machine learning techniques. Furthermore, he has worked on gene therapy applications in cancer drug discovery using siRNAs and microRNAs.
Dr. Yidong Chen received his B.S./M.S. degrees in Electrical Engineering from Fudan University, Shanghai, China, and a Ph.D. in Imaging Science from Rochester Institute of Technology, Rochester, NY. He has been with Hewlett Packard Co as a Research Engineer before he joined the National Institutes of Health (NIH) at 1996. At NIH, Dr. Chen joined the microarray technology development effort in the National Human Genome Research Institute (NHGRI) as a Special Expert, Staff Scientist, and later Associate Investigator for microarray imaging, statistical analysis, and bioinformatics. Currently, the Chen lab is working in the fields of computational biology and bioinformatics and focuses on developing computational solutions and statistical models to bridge the gap between quantitative science and basic biological and translational research within the Greehey Children’s Cancer Research Institute and around UT Health San Antonio.
