Thompson Rivers University

Yan Yan

Name: Dr. Yan Yan
Position: Assistant Professor
Phone:
Email: yyan@tru.ca

Research Interests

Bioinformatics, Machine Learning, Complex Network and Big Data Analysis

Education

Doctor of Philosophy (Biomedical Engineering), University of Saskatchewan (UofS), Saskatoon, SK
*Thesis "Computational methods for de novo peptide sequencing via tandem mass spectrometry"

Bachelor of Science (Mathematics and Computing Science), Northwestern Polytechnical University, Xi'an, P.R.China

Publications

Refereed journal papers
[J10] G. Dagasso, Y Yan, L Wang, L Li, R Kutcher, W Zhang, and L Jin. (2021): Leveraging Machine Learning to Advance Genome-Wide Association Studies. International Journal of Data Mining and Bioinformatics, accepted.
[J9] J Shi, Y Yan, M Links, L Li, J Dillon, M Horsch, AJ Kusalik (2019): Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection, BMC Bioinformatics, 20(Suppl15): 535.
[J8] Y Yan, C Burbridge, J Shi, J Liu, AJ Kusalik (2019): Effects of Input Data Quantity on Genome-Wide Association Studies (GWAS), International Journal of Data Mining and Bioinformatics, 22(1), 19-43.
[J7] Y Yan, AJ Kusalik, FX Wu (2017): NovoExD: De novo peptide sequencing for ETD/ECD spectra, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 14(2), 337-344.
[J6] Y Yan and K Zhang (2016). Spectra library assisted de novo peptide sequencing for HCD and ETD spectra pairs, BMC Bioinformatics, 17(17): 205-211.
[J5] Y Yan, AJ Kusalik, FX Wu (2016): De novo Peptide Sequencing using CID and HCD Spectra Pairs, Proteomics, 16(20): 2615-2624.
[J4] Y Yan, AJ Kusalik, FX Wu (2015): Recent developments in computational methods for de novo peptide sequencing from tandem mass spectrometry (MS/MS). Protein and peptide letters, 22(11): 983-991.
[J3] Y Yan, AJ Kusalik, FX Wu (2015): A framework of de novo peptide sequencing for multiple tandem mass spectra. IEEE Transactions on NanoBioscience, 14(4):478-484.
[J2] Y Yan, AJ Kusalik, FX Wu(2014): NovoHCD: De novo peptide sequencing from HCD spectra, IEEE Transactions on NanoBioscience, 13(2): 65-72.
[J1] Y Yan, S Zhang and FX Wu (2011): Applications of Graph Theory in Protein Structure Identification, Proteome Science, 9(S1:S17): 1-10.

Peer-reviewed conference proceedings
[C6] G. Dagasso, Y Yan, L Wang, L Li, R Kutcher, W Zhang, and L Jin. (2020): Comprehensive-GWAS: a pipeline for genome-wide association studies utilizing cross-validation to assess the predictivity of genetic variations, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2020, pp. 1361-1367
[C5] Y Yan, C Burbridge, J Shi, J Liu, AJ Kusalik (2018): Comparing Four Genome-Wide Association Study (GWAS) Programs with Varied Input Data Quantity, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2018: 1802-1809.
[C4] Y Yan, AJ Kusalik, FX Wu (2014): NovoPair: de novo peptide sequencing for complementary spectra pair, BIBM 2014: 150-155.
[C3] Y Yan, AJ Kusalik, FX Wu (2014): NovoGMET: De Novo Peptide Sequencing using Graphs with Multiple Edge Types (GMET) for ETD/ECD Spectra, International Symposium on Bioinformatics Research and Applications (ISBRA) 2014: 200-211
[C2] Y Yan, AJ Kusalik, FX Wu(2013): A multi-edge graph-based de novo peptide sequencing method for HCD spectra, BIBM 2013: 176-181.
[C1] B Chen, Y Yan, J Shi, S Zhang, FX Wu (2011): Improved graph entropy-based method for detecting protein complexes, BIBM 2011: 123-126.

Abstracts & Posters
[P4] Y Yan, C Burbridge, AJ Kusalik (2018): Tracking Top 20 Associations from Four Genome-Wide Association Study (GWAS) Programs with Varied Input Data Quantity, Plant and Animal Genome (PAG) conference 2018 (San Diego, USA).
[p3] Y Yan, C Burbridge, AJ Kusalik (2018): Tracking Associations from Four Genome-Wide Association Study (GWAS) Programs with Varied Input Data Quantity, RECOMB-genetics 2018 (Paris, France).
[P2] C Burbridge, Y Yan, AJ Kusalik (2017): Comparison of Genome-Wide Association Results With Varied p-Value Thresholds and Input Data Quantity, 2nd Annual P2IRC Symposium in 2017 (Saskatoon, Canada).
[P1] C Burbridge, Y Yan, AJ Kusalik (2017): Tracking Top 20 Genome-Wide Associations Using Three Programs With Varied Input Data Quantity, 2nd Annual P2IRC Symposium in 2017 (Saskatoon, Canada).

Employment History

Assistant Professor (June 2020 till Now) Department of Computing Science, Thompson Rivers University (TRU), Kamloops, BC

Postdoc Fellow (February 2017 to August 2019) Department of Computer Science, UofS, Saskatoon, SK
*Project: Genotype & Environment to Phenotype (GE2P) of Plant Phenotyping and Imaging Research Centre (P2IRC) (https://p2irc.usask.ca/) supported by Canada First Research Excellence Fund (CFREF)
*Research areas: Genome wide association studies (GWAS), mixed linear models, machine learning, statistical inference

Postdoc Fellow (October 2015 to September 2016) Department of Computer Science, University of Western Ontario, London, ON
*Research area: Computational algorithm development for sequence prediction utilizing multiple biological data source and forms

Courses Taught

TRU
- COMP4980 Introduction to Bioinformatics and Computational Biology
- DASC 6310 Data Analysis in Biology and Life Science (new course)
- COMP 3130 Formal Language
- COMP 2120 Programming Methods
UofS
- BINF210 Introduction to Bioinformatics Applications, Fall 2018

Timetable

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