Search Results for author: Fuhai Li

Found 12 papers, 6 papers with code

OmniCellTOSG: The First Cell Text-Omic Signaling Graphs Dataset for Joint LLM and GNN Modeling

1 code implementation2 Apr 2025 Heming Zhang, Tim Xu, Dekang Cao, Shunning Liang, Lars Schimmelpfennig, Levi Kaster, Di Huang, Carlos Cruchaga, Guangfu Li, Michael Province, Yixin Chen, Philip Payne, Fuhai Li

These systems evolve under influences such as age, sex, diet, environmental exposures, and diseases, making them challenging to decode given the involvement of tens of thousands of genes and proteins.

KoGNER: A Novel Framework for Knowledge Graph Distillation on Biomedical Named Entity Recognition

no code implementations19 Mar 2025 Heming Zhang, Wenyu Li, Di Huang, Yinjie Tang, Yixin Chen, Philip Payne, Fuhai Li

In this work, we introduce Knowledge Graph distilled for Named Entity Recognition (KoGNER), a novel approach that integrates Knowledge Graph (KG) distillation into NER models to enhance entity recognition performance.

Knowledge Distillation Knowledge Graphs +4

GraphSeqLM: A Unified Graph Language Framework for Omic Graph Learning

1 code implementation20 Dec 2024 Heming Zhang, Di Huang, Yixin Chen, Fuhai Li

The integration of multi-omic data is pivotal for understanding complex diseases, but its high dimensionality and noise present significant challenges.

Data Integration Graph Learning +2

Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer

no code implementations11 Feb 2024 Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael A Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li

However, we found two major limitations of existing GNNs in omics data analysis, i. e., limited-prediction (diagnosis) accuracy and limited-reproducible biomarker identification capacity across multiple datasets.

Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman

1 code implementation NeurIPS 2023 Jiarui Feng, Lecheng Kong, Hao liu, DaCheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen

We theoretically prove that even if we fix the space complexity to $O(n^k)$ (for any $k\geq 2$) in $(k, t)$-FWL, we can construct an expressiveness hierarchy up to solving the graph isomorphism problem.

Graph Regression

How Powerful are K-hop Message Passing Graph Neural Networks

1 code implementation26 May 2022 Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

Recently, researchers extended 1-hop message passing to K-hop message passing by aggregating information from K-hop neighbors of nodes simultaneously.

PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

1 code implementation19 Mar 2022 Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

In this work, we propose a Parallelizable Attention-based Computation structure Encoder (PACE) that processes nodes simultaneously and encodes DAGs in parallel.

Neural Architecture Search

Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare

no code implementations14 May 2021 Zehao Dong, Heming Zhang, Yixin Chen, Fuhai Li

Though deep learning algorithms are widely used in the drug synergy prediction problem, it is still an open problem to formulate the prediction model with biological meaning to investigate the mysterious mechanisms of synergy (MoS) for the human-AI collaboration in healthcare systems.

Graph Neural Network Prediction

Repurposing drugs for COVID-19 based on transcriptional response of host cells to SARS-CoV-2

1 code implementation1 Jun 2020 Fuhai Li, Andrew P. Michelson, Randi Foraker, Ming Zhan, Philip R. O. Payne

Based on the identified signaling pathways and GOs, a set of potentially effective drugs were repurposed by integrating the drug-target and reverse gene expression data resources.

Cannot find the paper you are looking for? You can Submit a new open access paper.