Projects per year
Personal profile
Personal profile
Zhen Wei is a bioinformatician who joined the faculty at the Department of Biological Sciences at Xi’an Jiaotong-Liverpool University in 2020. His current research focuses on the batch effect normalization techniques in NGS data, including their applications in various novel functional genomic technologies. He is also interested in developing novel predictive models and integrative databases in RNA genomics.
Research interests
Technical artifact correction in high-throughput sequencing: understanding technical biases in NGS assays using AI or statistical approaches; developing computational pipelines to detect and correct technical artifacts in various NGS datasets.
Investigating the effects of technical biases on biological conclusions: exploring improvement of biological conclusions following the correction of major technical artifacts in published NGS studies.
AI modeling for the integration of genomic markers: contributing to the development and rigorous benchmarking of high-performance machine learning and deep learning models to predict genomic molecular markers, such as DNA, RNA, and protein modifications, which are distributed non-randomly across genomic coordinates.
Software development in R/Bioconductor for genomic data science: building software packages in R with high usability and active maintenance that facilitate accurate, bias-corrected data analysis for biological signal calling and differential comparison.
Functional variant inference: understanding associative or causal relationships between genetic variants and various molecular modifications and human diseases from HTP assays using QTL or Mendelian Randomization.
Experience
Assistant Professor in Bioinformatics, XJTLU, 2020 to present
Program Director of BSc Bioinformatics, XJTLU, 2022 to present
Teaching
Module Leader, BIO214 Bioinformatics-II, 2020 to present
Module Leader, BIO215 Bioinformatics Project, 2024 to present
Co-lecturer, BIO316 High-throughput Approaches and Systems Biology, 2020 to present
Co-lecturer, APH003 Exploring the World Through Data, 2022 to present
Co-lecturer, BIO303 Final Year Project, 2020 to present
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD in Bioinformatics, University of Liverpool - 2020
Research areas
- Bioinformatics
- Machine Learning
- Deep Learning
- Genomic Data Science
- Statistical Modeling
Person Types
- Staff
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Development of bioinformatics methods for MeRIP-Seq analysis
1/01/23 → 31/12/25
Project: Internal Research Project
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Suzhou Municipal Key Lab for Intelligent Virtual Engineering
Yue, Y., Liang, H. N., Lim, E. G., Man, K. L., Ma, F., Wang, X., Guan, S., Wang, Q., Xiao, J., Ma, J., Meng, J., Zhang, C., Chen, M., Chen, B., Wang, W., Craig, P., Sun, J., Liu, G., Xia, J., Zhu, X., Yu, L., Zhang, J., Qi, J., Huang, M., Yang, R., Li, S., Dong, Y., Yang, X., Li, Y., Wang, J., Zhang, H., Wei, Z., Sun, Q., Elsheikh, A., Levers, A., Konev, B., Coenen, F., Atkinson, K., Gasieniec, L., Wong, P., Payne, T., Garcia-Fernandez, A. & Zhang, Y.
1/11/22 → 30/10/25
Project: Governmental Research Project
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Suzhou Municipal Key Lab for Metabolic Syndrome Drug Research
Meng, J., Meng, W., Jiang, X., Wei, Z., Li, T., Liu, X., Su, J., Yue, C., Douroudis, K., Kappes, F., Park, J., Wang, M., Rong, R., Raju, S., Huang, X., Kadowaki, T., OConnor, D., Lu, Z., Feng, Q., Yi, Y., Chen, Y., Jiang, B., Yuan, X., Cui, J., Meng, S., Smith, G., Loh, B. & 李荪
1/01/22 → 31/12/23
Project: Governmental Research Project
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Deciphering the genetic interplay between depression and dysmenorrhea: a Mendelian randomization study
Liu, S., Wei, Z., Carr, D. F. & Moraros, J., Jan 2025, In: Briefings in Bioinformatics. 26, 1Research output: Contribution to journal › Article › peer-review
Open Access -
Evaluating the Reliability of Machine Learning Predictors in m6A-SNP Association Analysis: A Comparative Study Using m6A-QTL Data
Mao, Z. & Wei, Z., 2024, (Accepted/In press) In: Current Bioinformatics.Research output: Contribution to journal › Article › peer-review
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Evaluating the Reliability of Machine Learning Predictors in m6A-SNP Association Analysis: A Comparative Study Using m6A-QTL Data
Mao, Z. & Wei, Z., 2024, (Accepted/In press) In: Current Bioinformatics.Research output: Contribution to journal › Article › peer-review
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Interpretable deep cross networks unveiled common signatures of dysregulated epitranscriptomes across 12 cancer types
Xia, R., Yin, X., Huang, J., Chen, K., Ma, J., Wei, Z., Su, J., Blake, N., Rigden, D. J., Meng, J. & Song, B., 10 Dec 2024, In: Molecular Therapy Nucleic Acids. 35, 4, 102376.Research output: Contribution to journal › Article › peer-review
Open Access -
m 6 A-Atlas v2.0: updated resources for unraveling the N 6 -methyladenosine (m 6 A) epitr anscript ome among multiple species
Liang, Z., Ye, H., Ma, J., Wei, Z., Wang, Y., Zhang, Y., Huang, D., Song, B., Meng, J., Rigden, D. J. & Chen, K., 5 Jan 2024, In: Nucleic Acids Research. 52, D1, p. D194-D202Research output: Contribution to journal › Article › peer-review
Open Access
Activities
- 2 Consultancy
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Interviewed by CNN Health for a feature titled "Study Reveals a Strong Genetic Connection Between Period Pain and Depression"
John Moraros (Consultant), Shuhe Liu (Consultant), Zhen Wei (Consultant) & Daniel F Carr (Consultant)
29 Nov 2024Activity: Consultancy
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BBC Sounds: Exploring the Question "Do People Experiencing Depression Have Worse Period Pain?"
John Moraros (Consultant), Shuhe Liu (Consultant), Zhen Wei (Consultant) & Daniel F Carr (Consultant)
27 Nov 2024Activity: Consultancy