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Ming-Ying Leung
Title Director of Bioinformatics and Computational Science Programs; Director of Bioinformatics Core, Border Biomedical Research Center
Faculty Rank Professor
Degree Ph.D.
Institution University of Texas at El Paso
Department Mathematical Sciences
Clusters Informatics
Department of Mathematical Sciences
The University of Texas at El Paso
City El Paso
State TX
Postal Code 79968
Telephone (915)747-6836
Fax (915)747-6502
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  My research focuses on developing probabilistic modeling and computational algorithms for bioinformatics analysis of biomolecular sequence data. In particular, I have developed Markov models, scan statistics, and computational algorithms to identify unusual palindromic patterns in the nucleotide sequences and have applied them to the analysis of genomic sequences of DNA and RNA viruses like the herpesviruses and SARS coronaviruses. I have also been developing efficient computational approaches for predicting secondary structures, including pseudoknots, of long RNA sequences. We have devised methods to circumvent the extremely high demands of memory and computing time in the structure prediction problem by using grid computing technologies available in the UTEP Border Biomedical Research Center Bioinformatics Computing Core Facility, where I serve as director. The research in these projects has resulted in several bioinformatics software packages publicly accessible online ( With broad research interests and experience in probabilistic modeling, algorithm design, and statistical bioinformatics, I have served as PI and co-PI in various projects for setting up and managing computational facilities for biomedical research and as director of the Bioinformatics and Computational Science Programs for administering graduate research training at UTEP. Over the past 20 years, my research has been funded by NIH, NSF, IBM, and the Texas NHARP in viral genome replication, sequence analysis, and RNA structural prediction with a long record of publication in these areas. In addition, I am involved in several collaborative research projects in identifying protein biomarkers for hepatocellular carcinoma, mammogram image analysis, HIV vaccine development, and pipeline implementation for bioinformatics analysis of exonic sequence variants in cancer-related genes.

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Availability Date:
Tuesday, March 01, 2016

I am currently serving as the director and graduate advisor for the MS Bioinformatics and PhD in Computational Science programs, which involve faculty in 10 different departments in science and engineering. I have been advisor to over 100 MS and 30 PhD students, many of whom have been trained in my research projects funded by NIH, NSF, and USDA and then gone on to professional careers at prestigious institutions like MD Anderson Cancer Center, Lawrence Berkeley National Lab, Stanford University, US Army Medical Research Institute of Infectious Disease, Hewlett Packard, Monsanto, and Pfizer. I have also mentored two postdoctoral fellows in 2005 - 2009, who went on to become faculty at the University of Maryland and software engineer at Amazon. In addition, in the past 10 years, I have been an appointed faculty mentor for three tenure-track faculty members at UTEP. Two of them are tenured full and associate professors now. The third one is an assistant professor who joined UTEP in 2014 and is PI of an NSF grant awarded in 2015. I have also served as a collaborator in several NIH-funded pilot projects with junior faculty as PI.

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1. Munoz S, Guerrero FD, Kellogg A, Heekin AM, Leung MY. Bioinformatic prediction of G protein-coupled receptor encoding sequences from the transcriptome of the foreleg, including the Haller's organ, of the cattle tick, Rhipicephalus australis. PLoS One. 2017; 12(2):e0172326.
2. Guerrero FD, Kellogg A, Ogrey AN, Heekin AM, Barrero R, Bellgard MI, Dowd SE, Leung MY. Prediction of G protein-coupled receptor encoding sequences from the synganglion transcriptome of the cattle tick, Rhipicephalus microplus. Ticks Tick Borne Dis. 2016 07; 7(5):670-677.
3. Zhang B, Yehdego DT, Johnson KL, Leung MY, Taufer M. Enhancement of accuracy and efficiency for RNA secondary structure prediction by sequence segmentation and MapReduce. BMC Struct Biol. 2013; 13 Suppl 1:S3.
4. Yehdego DT, Zhang B, Kodimala VK, Johnson KL, Taufer M, Leung MY. Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce. IEEE Int Symp Parallel Distrib Process Workshops Phd Forum. 2013 May; 2013:520-529.
5. Cruz-Cano R, Lee ML, Leung MY. Logic minimization and rule extraction for identification of functional sites in molecular sequences. BioData Min. 2012 Aug 16; 5(1):10.
6. Schaubert KL, Price DA, Salkowitz JR, Sewell AK, Sidney J, Asher TE, Blondelle SE, Adams S, Marincola FM, Joseph A, Sette A, Douek DC, Ayyavoo V, Storkus W, Leung MY, Ng HL, Yang OO, Goldstein H, Wilson DB, Kan-Mitchell J. Generation of robust CD8+ T-cell responses against subdominant epitopes in conserved regions of HIV-1 by repertoire mining with mimotopes. Eur J Immunol. 2010 Jul; 40(7):1950-62.
7. Licon A, Taufer M, Leung MY, Johnson KL. A Dynamic Programming Algorithm for Finding the Optimal Segmentation of an RNA Sequence in Secondary Structure Predictions. 2nd Int Conf Bioinform Comput Biol (2010). 2010 Mar; 2010:165-170.
8. Rosskopf JJ, Upton JH, Rodarte L, Romero TA, Leung MY, Taufer M, Johnson KL. A 3' terminal stem-loop structure in Nodamura virus RNA2 forms an essential cis-acting signal for RNA replication. Virus Res. 2010 Jun; 150(1-2):12-21.
9. Taufer M, Licon A, Araiza R, Mireles D, van Batenburg FH, Gultyaev AP, Leung MY. PseudoBase++: an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots. Nucleic Acids Res. 2009 Jan; 37(Database issue):D127-35.
10. Taufer M, Leung MY, Solorio T, Licon A, Mireles D, Araiza R, Johnson KL. RNAVLab: A virtual laboratory for studying RNA secondary structures based on grid computing technology. Parallel Comput. 2008 Nov 01; 34(11):661-680.
11. Chew DS, Leung MY, Choi KP. AT excursion: a new approach to predict replication origins in viral genomes by locating AT-rich regions. BMC Bioinformatics. 2007 May 21; 8:163.
12. Chew DS, Choi KP, Leung MY. Scoring schemes of palindrome clusters for more sensitive prediction of replication origins in herpesviruses. Nucleic Acids Res. 2005 Sep 01; 33(15):e134.
13. McMullin BT, Leung MY, Shanbhag AS, McNulty D, Mabrey JD, Agrawal CM. Correlating subjective and objective descriptors of ultra high molecular weight wear particles from total joint prostheses. Biomaterials. 2006 Feb; 27(5):752-7.
14. Leung MY, Choi KP, Xia A, Chen LH. Nonrandom clusters of palindromes in herpesvirus genomes. J Comput Biol. 2005 Apr; 12(3):331-54.
15. Chew DS, Choi KP, Heidner H, Leung MY. Palindromes in SARS and Other Coronaviruses. INFORMS J Comput. 2004; 16(4):331-340.
16. Leung MY, Marsh GM, Speed TP. Over- and underrepresentation of short DNA words in herpesvirus genomes. J Comput Biol. 1996; 3(3):345-60.
17. Leung MY, Blaisdell BE, Burge C, Karlin S. An efficient algorithm for identifying matches with errors in multiple long molecular sequences. J Mol Biol. 1991 Oct 20; 221(4):1367-78.
18. Karlin S, Morris M, Ghandour G, Leung MY. Algorithms for identifying local molecular sequence features. Comput Appl Biosci. 1988 Mar; 4(1):41-51.
19. Karlin S, Morris M, Ghandour G, Leung MY. Efficient algorithms for molecular sequence analysis. Proc Natl Acad Sci U S A. 1988 Feb; 85(3):841-5.

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1. Leung MY, Knapka JA, Wagler AE, Rodriguez G, Kirken RA. OncoMiner: A pipeline for bioinformatics analysis of exonic sequence variants in cancer. In: Big Data Analytics in Genomics, Wong KC (editor); Springer, New York, NY. 2016; 373-396.

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