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Sing-Hoi Sze

Sze, Sing-Hoi
Sing-Hoi Sze
Associate Professor of Computer Science and Engineering
Office:
HRBB / Room 328B
Email:
Phone:
979-458-3396
Undergraduate Education
B.Sc. Chinese University of Hong Kong (1990)
Graduate Education
M.S. Pennsylvania State University (1995)
Ph.D. University of Southern California (2000)
Postdoc. University of California-San Diego (2001-02)
Joined Texas A&M in 2002

Bioinformatics / Computational Biology

Our work focuses on the application of various computer science techniques to solve computational problems in molecular biology. Our current research projects cover diverse areas in bioinformatics, including motif finding algorithms and their applications, computational approaches to model transcription factor binding sites, and algorithms for EST sequence assembly and enumeration of alternatively spliced variants of a gene.

The motif finding problem can be formulated as follows: given a set of sequences, find a pattern (motif) shared by these sequences. The major biological application of this computational problem is to identify transcription factor binding sites given a set of upstream sequences of genes that are believed to be co-regulated. Existing motif finding approaches usually make simplifying assumptions in modeling these sites and we are on a constant quest to develop better models. Recently, we work with a few groups of biologists on designing experiments to verify our predictions.

Another active research project is the identification of alternatively spliced variants of a gene from EST sequences. The traditional approach to this problem is to assemble EST sequences that represent fragments of a gene into a longer linear sequence which represents the most dominant form of the gene. In order to better model the splicing structure, we develop an algorithm to assemble the given set of EST sequences into a non- linear graph structure, so that each alternatively spliced variant of a gene is represented as a path in the graph.

Recent Publications

  1. Qiu, C, Erinne, OC, Dave, JM, Cui, P, Jin, H, Muthukrishnan, N et al.. High-Resolution Phenotypic Landscape of the RNA Polymerase II Trigger Loop. PLoS Genet. 2016;12 (11):e1006321.
    doi: 10.1371/journal.pgen.1006321. PubMed PMID:27898685. PubMed Central PMC5127505.

  2. Yuan, Y, Zhang, Y, Fu, S, Crippen, TL, Visi, DK, Benbow, ME et al.. Genome Sequence of a Proteus mirabilis Strain Isolated from the Salivary Glands of Larval Lucilia sericata. Genome Announc. 2016;4 (4):.
    doi: 10.1128/genomeA.00672-16. PubMed PMID:27469950. PubMed Central PMC4966454.

  3. Fu, S, Tarone, AM, Sze, SH. Heuristic pairwise alignment of de Bruijn graphs to facilitate simultaneous transcript discovery in related organisms from RNA-Seq data. BMC Genomics. 2015;16 Suppl 11 :S5.
    doi: 10.1186/1471-2164-16-S11-S5. PubMed PMID:26576690. PubMed Central PMC4652555.

  4. Edman, RM, Linger, RJ, Belikoff, EJ, Li, F, Sze, SH, Tarone, AM et al.. Functional characterization of calliphorid cell death genes and cellularization gene promoters for controlling gene expression and cell viability in early embryos. Insect Mol. Biol. 2015;24 (1):58-70.
    doi: 10.1111/imb.12135. PubMed PMID:25225046. .

  5. Sze, SH, Tarone, AM. A memory-efficient algorithm to obtain splicing graphs and de novo expression estimates from de Bruijn graphs of RNA-Seq data. BMC Genomics. 2014;15 Suppl 5 :S6.
    doi: 10.1186/1471-2164-15-S5-S6. PubMed PMID:25082000. PubMed Central PMC4120145.

  6. Radulović, ŽM, Kim, TK, Porter, LM, Sze, SH, Lewis, L, Mulenga, A et al.. A 24-48 h fed Amblyomma americanum tick saliva immuno-proteome. BMC Genomics. 2014;15 :518.
    doi: 10.1186/1471-2164-15-518. PubMed PMID:24962723. PubMed Central PMC4099483.

  7. Hsieh, MF, Sze, SH. Finding alignments of conserved graphlets in protein interaction networks. J. Comput. Biol. 2014;21 (3):234-46.
    doi: 10.1089/cmb.2013.0130. PubMed PMID:24506222. .

  8. Fan, JH, Chen, J, Sze, SH. Identifying complexes from protein interaction networks according to different types of neighborhood density. J. Comput. Biol. 2012;19 (12):1284-94.
    doi: 10.1089/cmb.2012.0195. PubMed PMID:23210476. PubMed Central PMC3513984.

  9. Yi, G, Thon, MR, Sze, SH. Supervised protein family classification and new family construction. J. Comput. Biol. 2012;19 (8):957-67.
    doi: 10.1089/cmb.2011.0044. PubMed PMID:22876787. PubMed Central PMC3415071.

  10. Sze, SH, Dunham, JP, Carey, B, Chang, PL, Li, F, Edman, RM et al.. A de novo transcriptome assembly of Lucilia sericata (Diptera: Calliphoridae) with predicted alternative splices, single nucleotide polymorphisms and transcript expression estimates. Insect Mol. Biol. 2012;21 (2):205-21.
    doi: 10.1111/j.1365-2583.2011.01127.x. PubMed PMID:22283785. .

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