Welcome to Wan Lab@UNMC

Machine Learning and Bioinformatics (MLAB) Lab

The Wan Lab in the Department of Genetics, Cell Biology and Anatomy (GCBA) at University of Nebraska Medical Center (UNMC) is focusing on machine learning, bioinformatics, and computational biology, especially in single-cell analysis, multi-omics analysis, spatial transcriptomics, cancer research, intelligent healthcare, and precision medicine. To unravel the mechanisms of molecular biological systems in which enormous amounts of heterogeneous data are usually involved, bioinformatics and machine learning are perfect tools. Besides collaborating with scientists in cancer biology, metabolism, immunology, pathology and developmental biology, our laboratory is mainly to develop artificial intelligence, machine learning and/or data science-based methods to tackle essential biomedical problems in genomics, transcriptomics, epigenetics, proteomics, metabolomics, and interactomes as well as medical imaging data and electronic health records (EHR) data.

We are looking for passionate new PhD students, Postdocs, and Master students to join our team (more info) !

News

01-07-2026
Shibiao is invited to serve as a Session Chair for The 2026 International Conference on Intelligent Biology and Medicine (ICIBM 2026) to be held from Aug. 2-5, 2026 in Buffalo, NY. The link is here.

12-30-2025
Four abstracts from our lab are accepted in AACR Annual Meeting 2026. Congrats to Min-jeong, Bulidierxin, Nick and Lusheng!

12-29-2025
A research article preprint “MetaPaCS: A novel meta-learning framework for pancreatic cancer subtype identification” is online at bioRxiv. The link is here. Congratulations to Nick, Mengtao and Xinchao!

12-29-2025
Kevin Wang joins our lab as a research intern. Welcome aboard!

12-25-2025
A research article preprint “MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities” is online at bioRxiv. The link is here. Congratulations to Min-jeong and Lusheng!

12-18-2025
A research article preprint “A Multi-Modal Transfer Learning Framework to Reduce Health Disparities in Prostate Adenocarcinoma” is online at bioRxiv. The link is here. Congratulations to Lusheng!

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