1 code implementation • 2 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.
no code implementations • 19 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.
1 code implementation • 20 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.
no code implementations • 11 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.
no code implementations • 1 Sep 2023 • Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen
We theoretically reveal the trade-off of expressivity and stability in graph-canonization-enhanced GNNs.
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.
Ranked #3 on
Graph Regression
on ZINC-500k
no code implementations • 19 Sep 2022 • Zehao Dong, Heming Zhang, Yixin Chen, Philip R. O. Payne, Fuhai Li
Synergistic drug combinations provide huge potentials to enhance therapeutic efficacy and to reduce adverse reactions.
1 code implementation • 26 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.
1 code implementation • 19 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.
no code implementations • 14 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.
1 code implementation • 1 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.
no code implementations • 16 Nov 2018 • Tianyu Zhang, Liwei Zhang, Philip R. O. Payne, Fuhai Li
Drug resistance is still a major challenge in cancer therapy.