About Me

I completed my PhD in the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. My research interests focus on developing statistical and computational methods for omics data.
Email: quang.thinh.trac{at}ki.se | Github: tracquangthinh | Scholar: tracquangthinh
Education
Year |
University |
Country |
2020 - 2024 |
PhD - Karolinska Institutet |
 |
2018 - 2019 |
Msc. - Japan Advanced Institute of Science and Technology |
 |
2013 - 2017 |
Bsc. - VNU University of Engineering and Technology |
 |
Publications
- Quang Thinh Trac, Emily Joyce, Fredrik Boulund, Fang Fang, Yudi Pawitan, and Trung Nghia Vu. Functional quantification of microbiome from metagenomics. In manuscript.
- Quang Thinh Trac*, Yue Huang*, Tom Erkers, Paivi ̈Ostling, Anna Bohlin, Albin ̈Osterroos, Mattias Vesterlund, Rozbeh Jafari, Ioannis Siavelis, Helena Backvall, Santeri Kiviluoto, Lukas M. Orre, Mattias Rantalainen, Janne Lehtio, Soren Lehmann, Olli Kallioniemi, Yudi Pawitan and Trung Nghia Vu. Pathway activation model for personalized prediction of drug synergy. eLife13:RP100071. https://doi.org/10.7554/eLife.100071.1.
- Quang Thinh Trac, Yudi Pawitan, Tian Mou, Tom Erkers, Paivi ̈Ostling, Anna Bohlin, Albin ̈Osterroos, Mattias Vesterlund, Rozbeh Jafari, Ioannis Siavelis, Helena Backvall, Santeri Kiviluoto, Lukas M. Orre, Mattias Rantalainen, Janne Lehtio, Soren Lehmann, Olli Kallioniemi, and Trung Nghia Vu. Prediction model for drug response of acute myeloid leukemia patients. npj Precis. Onc. 7, 32 (2023). https://doi.org/10.1038/s41698-023-00374-z.
- Quang Thinh Trac, Tingyou Zhou, Yudi Pawitan, Trung Nghia Vu, Discovery of druggable cancer-specific pathways with application in acute myeloid leukemia, GigaScience, Volume 11, 2022, giac091, https://doi.org/10.1093/gigascience/giac091.
- Dat Thanh Nguyen, Quang Thinh Trac, Thi-Hau Nguyen, Ha-Nam Nguyen, Nir Ohad, Yudi Pawitan, Trung Nghia Vu. Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data, BMC Bioinformatics 22, 495 (2021). https://doi.org/10.1186/s12859-021-04418-8
- Trung Nghia Vu, Wenjiang Deng, Quang Thinh Trac, Stefano Calza, WoochangHwang, Yudi Pawitan. A fast detection of fusion genes from paired-end RNA-seq data,BMC Genomics 2018 19:786. https://doi.org/10.1186/s12864-018-5156-1.
- Thanh Hai Dang*, Quang Thinh Trac*, Huy Kinh Phan, Manh Cuong Nguyen, Quynh Trang Pham Thi. SKIPHOS: non-kinase specific phosphorylation site prediction with random forests and amino acid skip-gram embeddings, biorxiv. https://doi.org/10.1101/793794.
* Authors contributed equally
Challenges
- CTD2 BeatAML DREAM Challenge
- Sub-challenge 1 (quantitative ex vivo drug sensitivity prediction): 3th in the primary metric.
- Sub-challenge 2 (clinical response prediction): 1st in the primary metric.
- Only team in top 3 in both sub-challenges