Publications and Presentations

Papers published  

(*: authors with equal contributions)

• Y.-C. Chen, H.-W. Chen, T.-Y. Liu, Y.-S. Juan, Y.-P. Liu, S.-L. Chen, C.-H. Lee, W.-C. Tsai, W.-J. Wu. Combination of skin sympathetic nerve activity and urine biomarkers in improving diagnostic accuracy for urge urinary incontinence. Scientific Reports, Vol. 15, No. 14117, 2025. [html]

• T.-Y. Yen, C. Hsu, N.-C. Lee, C.-S. Wu, H. Wang, K.-Y. Lee, C.-R. Lin, C.-Y. Lu, M.-L. Tsai, T.-Y. Liu, C. Lin, C.-Y. Chen, L.-Y. Chang, F. Lai, L.-M. Huang. Signatures of lower respiratory tract microbiome in children with severe community-acquired pneumonia using shotgun metagenomic sequencing, Journal of Microbiology, Immunology and Infection, 2024. [html]

• N. Wan, D. Weinberg, T.-Y. Liu, K. Niehaus, D. Delubac, A. Kannan, B. White, E. Ariazi, M. Bailey, M. Bertin, N. Boley, D. Bowen, J. Cregg, A. Drake, R. Ennis, S. Fransen, E. Gafni, L. Hansen, Y. Liu, G. L. Otte, J. Pecson, B. Rice, G. E. Sanderson, A. Sharma, J. St. John, C. Tang, A. Tzou, L. Young, G. Putcha, I. S. Haque. Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA, BMC cancer, Vol. 19, No. 1, pp. 1-10, 2019. [html]

• T.-Y. Liu*, A. Kannan*, A. Drake, M. Bertin, N. Wan. Bridging the Generalization Gap: Training Robust Models on Confounded Biological Data, workshop on Critiquing and Correcting Trends in Machine Learning, NeurIPS, 2018. [html]

• T.-Y. Liu*, H. H. Huang*, D. Wheeler, Y. Xu, J. A. Wells, Y. S. Song, A. P. Wiita.   Time-resolved proteomics extends ribosome profiling-based measurements of protein synthesis dynamics, Cell Systems, Vol. 4, No. 6, pp. 636-644, 2017. (This is a cover article.) [html]

• T.-Y. Liu, Y. S. Song.   Prediction of Ribosome Footprint Profile Shapes from Transcript Sequences, Bioinformatics,Vol. 32, No. 12, pp. i183-i191, doi:10.1093/bioinformatics/btw253, 2016. [html]

• T.-Y. Liu*, A. E. Dodson*, J. Terhorst, Y. S. Song and J. Rine.   Riches of Phenotype Computationally Extracted from Microbial Colonies, Proceedings of the National Academy of Sciences, Vol. 113, No. 20, pp. E2822-E2831, doi:10.1073/pnas.1523295113, 2016. [html]

• M. T. McClain, B. P. Nicholson, L. P. Park, T.-Y. Liu, A. O. Hero III, E. Tsalik, A. K. Zaas, T. Veldman, L. L. Hudson, R. Lambkin-Williams, A. Gilbert, G. S. Ginsburg and C. W. Woods.   A Genomic Signature of Influenza Infection Shows Potential for Presymptomatic Detection, Guiding Early Therapy, and Monitoring Clinical Responses, Open Forum Infectious Diseases, Vol. 3, No. 1, doi:10.1093/ofid/ofw007, 2016. [html]

• T.-Y. Liu, T. Burke, L. P. Park, C. W. Woods, A. K. Zaas, G. S. Ginsburg and A. O. Hero.   An individualized predictor of health and disease using paired reference and target samples, BMC bioinformatics, Vol. 17, No. 1, pp. 1-15, 2016. [html]

• T.-Y. Liu, A. Wiesel, and A. O. Hero.   A Sparse Multi-class Classifier for Biomarker Screening. Global Conference on Signal and Information Processing (GlobalSIP) Proceedings, IEEE, pp. 77-80, 2014.[html]

• A. Dufour, T.-Y. Liu, C. Ducroz, R. Tournemenne, B. Cummings, R. Thibeaux, N. Guillen, A. O. Hero III, and Jean-Christophe Olivo-Marin.   Signal Processing Challenges in Quantitative 3-D Cell Morphology. IEEE Signal Processing Magazine, pp. 30-40, 2014. [html]

• T.-Y. Liu, L. Trinchera, A. Tenenhaus, D. Wei, and A. O. Hero.   Globally Sparse PLS Regression. New Perspectives in Partial Least Squares and Related Methods, Springer Proceedings in Mathematics and Statistics, Vol. 56, pp. 117-127, 2013. [html]

• M. Yokokawa*, T.-Y. Liu*, K. Yoshida, C. Scott, A. O. Hero, E. Good, F. Morady, and F. Bogun.   Automated analysis of the 12-lead electrocardiogram to identify the exit site of postinfarction ventricular tachycardia. Heart Rhythm, Vol. 9, No. 3, pp. 330-334, 2012. [html]

• K. Yoshida*, T.-Y. Liu*, C. Scott, A. Hero, M. Yokokawa, S. Gupta, E. Good, F. Morady, F. Bogun.   The Value of Defibrillator Electrograms for Recognition of Clinical Ventricular Tachycardias and for Pace-Mapping Of Post-Infarction Ventricular Tachycardia. Journal of the American College of Cardiology, Vol. 56, No. 12, pp. 969-979, 2010. [html]

• T. S. Baman, D. C. Lange, K. J. Ilg, S. K. Gupta, T.-Y. Liu, C. Alguire, W. Armstrong, E. Good, A. Chugh, K. Jongnarangsin, F. Pelosi Jr., T. Crawford, M. Ebinger, H. Oral, F. Morady, F. Bogun.   Relationship between burden of premature ventricular complexes and left ventricular function. Heart Rhythm Vol. 7, No. 7, pp. 865-869, 2010. [html]

Ph.D. dissertation

• Statistical Learning for Sample-Limited High-dimensional Problems with Application to Biomedical Data. (Advisor: Professor Alfred O. Hero III; co-advisor: Professor Clayton D. Scott.)

Conference Presentations, including talks and posters

• T.-Y. Liu, T.-H. Sun, C.-K. Lai, S.-J. Tu, Y.-X. Huang, M.-H. Wu, C.-L. Hung, C.-H. Lien, S.-F. Wang, K.-C. Hsu, E. Chuang, "Accelerate Drug Discovery for Amyotrophic Lateral Sclerosis Using BioNeMo Framework", Nvidia GTC, 2025. 

• F. Vallania, V. Cheung, M. D. Zamba, J. Liu, A. Pasupathy, H. Donnella, M. Bailey, M. Louie, J. Lin, K. Havenith, Y. Qin, S. Pantano, J. Wuerthner, P. H.van Berkel. "Identification of predictive biomarkers for response of R/R DLBCL patients treated with loncastuximab tesirine using low-pass whole-genome cell-free DNA sequencing (cfDNA-WGS)",  American Society of Hematology (ASH) Annual Meeting, 2022.

• T.-K. Hsu , T.-Y. Liu, B. Gould, C. Decapite, A. Zureikat, A. Paniccia, E. Ariazi, M. Bertin, R. Bourgon, K. Coil, H. Donnella, A. Drake, J. M. Granka, P. Kaur, M. C. Louie, A. Pasupathy, O. Shapira, P. Ulz, C. Yang, C. J. Lin, R. Brand. "Plasma-based detection of pancreatic cancer: A multiomics approach", American Association for Cancer Research (AACR) Virtual Special Conference: Pancreatic Caner, 2021.

• C. J. Lin, E. Ariazi, M. Dzamba, T.-K. Hsu, S. Kothen-Hill, K. Li, T.-Y. Liu, S. Mahajan, K. K. Palaniappan, A. Pasupathy, A. Polonskaia, J. St. John, D. Steiger, P. Ulz, I. Wang, J. Xiao, R. Yang, G. Putcha, and A. Shaukat. ”Evaluation of a sensitive blood test for the detection of colorectal advanced adenomas in a prospective cohort using a multiomics approach”, American Society of Clinical Oncology GI, 2021.

• F. Vallania, H. Warsinske, P. Ulz, T.-Y. Liu, K. Assayag, K. K. Palaniappan, M. Bailey, I. Wang, D. Weinberg, R. Ennis, C. J. Lin, A.-M. Martin and N. Krunic. ”Multi-omic plasma profiling identifies potential signatures of disease progression in early-stage NSCLC”, American Association for Cancer Research, 2020.

• G. Putcha, T.-Y. Liu, E. Ariazi, M. Bertin, A. Drake, M. Dzamba, G. Hogan, S. Kothen-Hill, J. Liao, K. Li, S. Mahajan, K. Palaniappan, P. Sansanwal, J. St John, P. Ulz, N. Wan, H. Warsinske, D. Weinberg, R. Yang and C. J. Lin. ”Blood-Based Detection of Early-Stage Colorectal Cancer Using Multiomics and Machine Learning”, American Society of Clinical Oncology GI, 2020.

• T.-Y. Liu, F. Vallania, M. Dzamba, M. Bailey, C. Roberts, B. Engelhardt, C. J. Lin. "Latent Representations from Factor Analysis and CNNs of Genomic and Proteomic Data Reveal Immune Pathways Involved in Colorectal Cancer", workshop on Learning Meaningful Representations of Life, NeurIPS, 2019.

• N. Wan, D. Weinberg, T.-Y. Liu, K. Niehaus, D. Delubac, A. Kannan, B. White, E. Ariazi, M. Bailey, M. Bertin, N. Boley, D. Bowen, J. Cregg, A. Drake, R. Ennis, S. Fransen, E. Gafni, L. Hansen, Y. Liu, G. L. Otte, J. Pecson, B. Rice, G. E. Sanderson, A. Sharma, J. St. John, C. Tang, A. Tzou, L. Young, I. S. Haque, G. Putcha. "Machine Learning Enables Detection of Early-Stage Colorectal Cancer by Whole-Genome Sequencing of Plasma Cell-Free DNA", Digestive Disease Week, 2019.

• Y. Liu, T.-Y. Liu, D. E. Weinberg, C. J. De La Torre, C. L. Tan, A. D. Schmitt, S. Selvaraj, V. Tran, L. C. Laurent, L. Cabel, F.-C. Bidard,  G. Putcha, I. S. Haque. "Spatial co-fragmentation pattern of cell-free DNA recapitulates in vivo chromatin organization and identifies tissue-of-origin", AACR Annual Meeting, 2019.

• T.-Y. Liu, A. Kannan, A. Drake, M. Bertin, N. Wan. "Bridging the Generalization Gap: Training Robust Models on Confounded Biological Data, workshop on Critiquing and Correcting Trends in Machine Learning, NeurIPS, 2018.

• K. Niehous, N. Wan, B. White, A. Kannan, E. Gafni, T.-Y. Liu, I. Haque, G. Putcha. "Early Stage Colorectal Cancer Detection Using Artificial Intelligence and Whole-Genome Sequencing of Cell-Free DNA in a Retrospective Cohort of 1,040 Patients". ACG 2018 Annual Scientific Meeting, 2018.

• T.-Y. Liu, H. H. Huang, D. Wheeler, Y. Xu, J. A. Wells, Y. S. Song, A. P. Wiita. "Translational dynamics revealed by ribosome occupancy and time-resolved proteomics during chemotherapeutic response".Cold Spring Harbor Meeting: The Biology of Genomes, 2017.

• T.-Y. Liu, Y. S. Song. "Prediction of Ribosome Footprint Profile Shapes from Transcript Sequences". Intelligent Systems for Molecular Biology (ISMB), 2016 (oral presentation).

• T.-Y. Liu, H. H. Huang, D. Wheeler, Y. S. Song, A. P. Wiita. "Direct measurement and modeling of protein synthesis and degradation dynamics during chemotherapeutic response in multiple myeloma". American Society for Mass Spectrometry (ASMS), 2016.

• T.-Y. Liu, Y. S. Song. "Prediction of Ribosome Footprint Distributions from Transcript Sequences via Multiresolution Analysis". Neural Information Processing Systems (NIPS) workshop on Machine Learning in Computational Biology (MLCB), 2015 (oral presentation).

• T.-Y. Liu, Y. S. Song. "Can you predict the shape of Ribosome profiles? Marginal Probability Density Estimation of Ribosome Footprints". Cold Spring Harbor Laboratory (CSHL) Probabilistic Modeling in Genomics, 2015.

• T.-Y. Liu, H. H. Huang, D. Wheeler, J. A. Wells, Y. S. Song, A. P. Wiita. "Integrative longitudinal analysis of ribosome occupancy and protein synthesis during chemotherapeutic response reveals complex translational dynamics". American Society of Human Genetics Annual Meeting (ASHG), 2015.

• T.-Y. Liu, A. Wiesel, and A. O. Hero. "A Sparse Multi-class Classifier for Biomarker Screening". Global Conference on Signal and Information Processing (GlobalSIP), IEEE, 2014.

• T.-Y. Liu, L. Trinchera, A. Tenenhaus, D. Wei, and A. O. Hero. "Global Criteria for Sparse Penalized Partial Least Squares". World Statistics Congress, 2013.

• T.-Y. Liu, L. Trinchera, A. Tenenhaus, D. Wei, and A. O. Hero."Globally Sparse PLS Regression with Application to Gene Expression Analysis". Information Theory and Applications Workshop (ITA), 2013.

• T.-Y. Liu, L. Trinchera, A. Tenenhaus, D. Wei, and A. O. Hero. "Globally Sparse PLS Regression". 7th International Conference on Partial Least Squares and Related Methods (PLS), 2012.

• T.-Y. Liu, A. Wiesel, C. W. Woods, A. Zaas, G. S. Ginsburg and A. O. Hero. " Learning Differential Gene Expression Signatures from Personalized High Throughput Screening". The Great Lakes Bioinformatics Conference, 2012.

• T.-Y. Liu, L. Trinchera, A. Tenenhaus, D. Wei, and A. O. Hero. "A new criterion for sparse PLS regression". Compstat, 2012.

Invited talks

• "Machine Learning for Oncology Care Management from risk assessment, diagnostic support, to treatment selection and development", Department of Clinical Laboratory Sciences and Medical Biotechnology Seminar, 2025. 

• "Accelerating Drug Discovery for Amyotrophic Lateral Sclerosis", International Conference on Quantum & AI Technologies in Biomedical Science, 2025.

• "Machine Learning for Oncology Care Management from risk assessment, diagnostic support, to treatment selection and development", TIGP Program on Bioinformatics Seminar, 2025. 

• "Machine Learning for Oncology Care Management from risk assessment, diagnostic support, to treatment selection and development", Department of Electrical Engineering Seminar, 2024. 

• "Plasma-Based Cancer Detection: A Machine Learning Enabled Multiomics Approach", TIGP Program on Bioinformatics Seminar, 2024. 

• “Blood-based early cancer detection using multiomics and machine learning”, BST Departmental Seminar in Science & Technology, National Taiwan University, 2023.

• “Blood-based early cancer detection using multiomics and machine learning”, Master's Program in Smart Medicine and Health Informatics, National Taiwan University, 2023.

• “Blood-based early cancer detection using multiomics and machine learning”, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, 2023.

• “Blood-based early cancer detection using multiomics and machine learning”, International Conference on Technologies and Applications of Artificial Intelligence, 2022.

• “Blood-based early cancer detection using multiomics and machine learning”, US-Taiwan Biomedical Engineering Forum, 2022.

• "Early cancer detection using Machine Learning", Research Center for Information Technology Innovation, Academia Sinica, 2021.

• "Early cancer detection using ML", MLBytes Speaker Series, Duke University, 2019.

• "Immune pathways revealed by machine learning using genomic and proteomic data of colorectal cancer", Bay Area Bioinformatics Forum meetup, PacBio, 2019.

• "Translational dynamics revealed by statistical signal processing for ribosome profiling data", Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, 2017.

• "Statistical learning methods for the study of translational dynamics", Department of Statistics and Biostatistics, Rutgers University, 2017.

• "Translation dynamics revealed by statistical learning for ribosome profiling data", Department of Statistics, University of California, Davis, 2017.

• "Study of translational regulation using ribosome profiling and pulse-chase isotopic labeling mass spectrometry-based proteomics", Department of Epidemiology and Biostatistics, University of California, San Francisco, 2016.

Past and Present Research Collaborators

• Andra Leah Blomkalns, Department of Emergency Medicine, Stanford University.

• Ting-Yun Huang, Emergency Department, Taipei Medical University Shuang Ho Hospital.

• Wen-Hung Kuo, Department of Surgery, National Taiwan University Hospital.

• Yi-Chun Wu, Institute of Molecular and Cellular Biology, National Taiwan University.

• Ting-Yu Yen, Department of Pediatrics, National Taiwan University Hospital.

• Sarah A. Tishkoff, Alessia Ranciaro, Eric Mbunwe, Departments of Genetics and Biology, University of Pennsylvania.

• Arun Wiita, Hector Huang, Dept Laboratory Medicine, University of California, San Francisco.

• Jasper Rine, Anne Dodson, Dept Molecular and Cell Biology, University of California, Berkeley.

• Indika Rajapakse, Dept Computational Medicine and Bioinformatics, University of Michigan.

• Geoffrey S. Ginsburg, Center for Applied Genomics and Precision Medicine, Dept Medicine, Duke University.

• Alexandre Dufour, Quantitative Image Analysis Unit, Institut Pasteur, France.

• Jean-Christophe Olivo-Marin, Quantitative Image Analysis Unit, Institut Pasteur, France.

• Laura Trinchera, Rouen Business School, Mont-Saint-Aignan, France.

• Arthur Tenenhaus, Department of Signal Processing and Electronic Systems, Supélec, Gif-sur-Yvette, France.

• Frank Bogun, Dept Cardiology, University of Michigan.