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 artificial intelligence (AI), machine learning (ML), 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, AI/ML and bioinformatics are perfect tools. Besides collaborating with scientists in cancer biology, metabolism, immunology, pathology and developmental biology, our laboratory is mainly to develop AI/ML 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

10-03-2026
A collaboration research article preprint titled “Predicting the Timing of Adolescent Drinking Onset from Baseline Clinical Data: A Stacked-Encoder Survival Framework with Embedding-Derived Biotypes” is online at medRxiv. The link is here.

10-02-2026
A research article titled “WIMOAD: Weighted Integration of Multi-Omics Data with Meta Learning for Alzheimer’s Disease Diagnosis” has been officially published by the Journal of Alzheimer’s Disease. The link is here. Congratulations to Hanyu!

09-30-2026
Shibiao attends and brings AI expertise to the inaugural UNL-UNMC Summit in Ashland, NE.

09-30-2026
The 2026 ISCB Great Plains Bioinformatics Conference (ISCB-Great Plains 2026), for which Shibiao serves as the Co-Chair for Poster Committee, has been successfully held from Sep. 28-30, 2026 in Omaha, NE. The link is here.

09-27-2026
A collaboration research article preprint titled “Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learning” is online at arXiv. The link is here.

09-22-2026
A review article titled “A Comprehensive Review on RNA Subcellular Localization Prediction” is accepted by the journal Briefings in Functional Genomics. Congratulations to Cece, Xuehuan and Nick!

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