Guanming Wu

The paper introduces the Vaccine Ontology (VO), a standardized framework for representing vaccines and related data, enhancing data integration and AI research.

This study identifies RUNX1 as a key driver of tumor-immune hybrid cell invasion and dissemination in colorectal cancer, highlighting circulating hybrid cells as a biomarker for metastasis.

This study shows HCMV uses UL8 and miR-UL36 to suppress Notch signaling, promoting reactivation in CD34+ hematopoietic progenitor cells.

The paper introduces a common data model and databases for integrating heterogeneous biomedical data, enabling cross-domain analysis and revealing sex-specific immune response insights.

This paper applies large language models to assist in gene annotation into Reactome pathways, showing promising results in supporting curation workflows.

MiroSCOPE is an AI platform for annotating functional tissue units in digital pathology, enabling efficient annotation of over 71,900 units across prostate cancer samples.

The paper analyzes GPCR signaling dysregulation in cancer transcriptomics data to identify therapeutic targets and survival-associated signaling axes.

This paper introduces Graph Structured Neural Networks (GSNN) for perturbation biology, showing they outperform baselines in predicting perturbed gene expression, drug combinations, and disease-specific drug prioritization.

The paper annotates disease variants in the context of biological pathways to infer molecular phenotypes and model variant impacts.

The paper develops a framework to analyze scRNA-seq data and identify gene-regulatory networks linked to CD8 T cell exhaustion in tumor and viral infection contexts.

This paper explores using ChatGPT in Reactome curation to automate pathway annotation, comparing its outputs to manual curation and identifying challenges and improvements.

The paper predicts functional interactions of dark proteins with Reactome pathways using a random forest classifier and develops a web portal to visualize these interactions.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

The paper identifies a dual state of Bmi1-expressing intestinal stem cells that drive epithelial development and tissue regeneration through dynamic Wnt signaling.

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.