Shibiao Wan

Asst. Prof. & Co-Director for BISB PhD Program at UNMC. Research Interests: AI/ML, Bioinformatics/Computational Biology, Cancer Research, Multi-Omics Analysis.

[Shibiao Wan @ShibiaoWan]

Congratulations to Mengtao! Based on our previous publication SAMP, we develop SAMP V2 that incorporates biochemical-sequence-order information into the split amino acid composition for a stacking meta-learning framework on accurate AMP identification.
https://t.co/Wwo2SPk2pY

[Shibiao Wan @ShibiaoWan]

Congratulations to Bulidierxin, Dr. Xiaoting Fan, and other coauthors! Glad to share that we have developed a novel meta-learning framework MetaAMI for accurate in-hospital mortality prediction for acute myocardial infarction (AMI).

https://t.co/GVxks1fbYh

[Shibiao Wan @ShibiaoWan]

This project will be performed under the collaboration between our lab at UNMC and our collaborators Dr. Daniel J. Robertson from University of Idaho and Dr. Rajandeep Sekhon from Clemson University. Look forward to starting this exciting project soon.

[Shibiao Wan @ShibiaoWan]

I am thrilled to share that we have been awarded a 4-year Focused EPSCoR Collaboration (FEC) Grant by NSF! In this project, our lab will develop a novel multi-modal foundation model for crop lodging prediction.
https://t.co/b6B5fCXarm

[Shibiao Wan @ShibiaoWan]

Congratulations to my PhD student Xinchao Wu being awarded this year's UNMC fellowship! This is a fantastic achievement given that the fellowship application is very competitive and he could obtain the fellowship for his first application. Well done, Xinchao!

[Shibiao Wan @ShibiaoWan]

OTTER could effectively integrate transcriptomics and genomics data for interpretable feature selection and cross-omics interaction exploration, eventually facilitating accurate T-ALL subtyping for potentially clinical applications.

[Shibiao Wan @ShibiaoWan]

Congratulations to Lusheng Li and other coauthors! Glad to share that we have developed an optimal-transport multi-omics integration framework called OTTER for accurate molecular characterization of T-cell acute lymphoblastic leukemia (T-ALL).

https://t.co/bXYihCNVqO

[Shibiao Wan @ShibiaoWan]

Specifically, we have demonstrated the superiority of PRIME over state-of-the-art approaches on diverse datasets including million-level single cell and ST data in terms of trajectory inference, spatial-domain preservation, and single-cell perturbation-response prediction.

[Shibiao Wan @ShibiaoWan]

Congratulations to Xinchao Wu and other coauthors! We have developed a novel method PRIME (Projection-based Robust Integration via Manifold Embedding) for atlas-level single-cell and spatial transcriptomics data integration.

https://t.co/wFQpNeIen1

[Shibiao Wan @ShibiaoWan]

2. Poster Presentation for AMIA 2026 Annual Symposium: Predicting In-Hospital Mortality in Acute Myocardial Infarction via a Novel Meta-Learning Approach Authors: Bulidierxin Tuerhanbayi, Xiaoting Fan, Jieqiong Wang, and Shibiao Wan

[Shibiao Wan @ShibiaoWan]

Glad to share that we have two pieces of work being accepted to two different conferences.

1. Oral Presentation for ISMB 2026:
A Palma Ratio–Driven Graph-Fusion Approach for Detecting Ultra-Rare Cell Types in scRNA-seq Data
Authors: Xingzhi Niu, Jieqiong Wang, and Shibiao Wan

[Shibiao Wan @ShibiaoWan]

Congratulations to my graduate student Nick Peterson for official graduation! Wish you all the best for your future career!

[Shibiao Wan @ShibiaoWan]

Excited to share that I have been elevated to be an ACM Senior Member. I am deeply grateful for the strong support from my mentors, collaborators, colleagues and my lab members and trainees.

[Shibiao Wan @ShibiaoWan]

Glad to see my graduate student Nick Peterson successfully defending his Final Oral Exam and will officially graduate next month. Time flies. I am sure you will have a bright future!

[Shibiao Wan @ShibiaoWan]

Abstract 1427: Exploring high-resolution subtypes for pancreatic ductal adenocarcinoma via a meta-clustering approach.

https://t.co/L91CGM5KyP

[Shibiao Wan @ShibiaoWan]

Happy to share that our lab will present four abstracts in 2026 AACR Annual Meeting at San Diego, CA in less than two weeks. Specifically, we have developed a series of AI/ML and bioinformatics approaches for pediatric glioma, T-ALL, breast cancer, and pancreatic cancer.

[Shibiao Wan @ShibiaoWan]

Abstract 4176: DAG-guided kernel learning framework to mitigate racial disparities in breast cancer

https://t.co/4MLIp7DsLB

[Shibiao Wan @ShibiaoWan]

Abstract 6904: OTTER: Optimal transport-based transcriptomics and genomics representation fusion for T-ALL subtyping.

https://t.co/khZqUqTDxG

[Shibiao Wan @ShibiaoWan]

Abstract 4177: Integrated meta-clustering reveals subtype-specific transcriptomic heterogeneity of pediatric low-grade glioma

https://t.co/qlRy12vzPf

[Shibiao Wan @ShibiaoWan]

Congratulations to Xingzhi Niu and other co-authors! We have developed a novel graph-fusion method called PalmaClust to leverage the Palma ratio to identify ultra-rare cell types from single cell data.

https://t.co/o9hIM40haI