Ming-Ying Leung

Ming-Ying Leung is a Professor in Mathematical Sciences at the University of Texas at El Paso (UTEP) and Director of the Bioinformatics and Computational Science Programs. Her career spans structural bioinformatics, RNA sequence analysis, and mathematical modeling of biomolecules.

• PhD in Mathematics, Stanford University (1989)
• MS in Computer Science, Stanford University (1988)

Her research focuses on probabilistic modeling and statistical bioinformatics, particularly Markov models and scan statistics for DNA sequence analysis. She develops algorithms to predict RNA secondary structures and functional genomic sites, with applications in agricultural science and biomedical research. Recently, her work has expanded to cancer genomics, studying single nucleotide variants in leukemia and prostate cancer, and GPCR ligand binding mechanisms across families.

Dr. Leung's funded projects include NSF, NIH, and USDA grants for genomic studies. She leads initiatives like Bioinformatics Education for Agricultural Science (BEAS), Bioinformatics Computing Laboratory (BCL), and Undergraduate Participation in Bioinformatics Training (UPBiT), emphasizing student research involvement.

• Student Choice Award for Outstanding Teaching (2017)
• Two Outstanding Performance Awards in Extramural Funding (2015, 2008)
• Professor Y.C. Wong Visiting Lectureship at University of Hong Kong (2004)
• Andrew Mellon Foundation Research Award (1986)

She mentors students through doctoral and graduate research courses, including Mathematical & Computational Modeling and Stochastic Processes. Her lab maintains tools like RNAVLab, ISOGlyP, and GPCR-PEnDB, advancing computational methods for genomic and structural analysis.