Search Results for author: Shuangjia Zheng

Found 13 papers, 7 papers with code

Effective Protein-Protein Interaction Exploration with PPIretrieval

no code implementations6 Feb 2024 Chenqing Hua, Connor Coley, Guy Wolf, Doina Precup, Shuangjia Zheng

Protein-protein interactions (PPIs) are crucial in regulating numerous cellular functions, including signal transduction, transportation, and immune defense.

Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction

1 code implementation12 May 2022 Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang

To address these problems, we propose a novel Communicative Subgraph representation learning for Multi-relational Inductive drug-Gene interactions prediction (CoSMIG), where the predictions of drug-gene relations are made through subgraph patterns, and thus are naturally inductive for unseen drugs/genes without retraining or utilizing external domain features.

Gene Interaction Prediction Representation Learning

Molecular Attributes Transfer from Non-Parallel Data

no code implementations30 Nov 2021 Shuangjia Zheng, Ying Song, Zhang Pan, Chengtao Li, Le Song, Yuedong Yang

Optimizing chemical molecules for desired properties lies at the core of drug development.

Attribute Style Transfer

Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis

no code implementations4 Sep 2021 Sijie Mai, Ying Zeng, Shuangjia Zheng, Haifeng Hu

Specifically, we simultaneously perform intra-/inter-modal contrastive learning and semi-contrastive learning (that is why we call it hybrid contrastive learning), with which the model can fully explore cross-modal interactions, preserve inter-class relationships and reduce the modality gap.

Contrastive Learning Multimodal Sentiment Analysis

Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning

no code implementations26 Jul 2021 Shuangjia Zheng, Sijie Mai, Ya Sun, Haifeng Hu, Yuedong Yang

In this way, we find the model can quickly adapt to few-shot relationships using only a handful of known facts with inductive settings.

Inductive Link Prediction Knowledge Graphs +2

Learning Attributed Graph Representations with Communicative Message Passing Transformer

1 code implementation19 Jul 2021 Jianwen Chen, Shuangjia Zheng, Ying Song, Jiahua Rao, Yuedong Yang

For this sake, we propose a Communicative Message Passing Transformer (CoMPT) neural network to improve the molecular graph representation by reinforcing message interactions between nodes and edges based on the Transformer architecture.

Inductive Bias molecular representation +1

Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction

2 code implementations1 Jul 2021 Jiahua Rao, Shuangjia Zheng, Yuedong Yang

Advances in machine learning have led to graph neural network-based methods for drug discovery, yielding promising results in molecular design, chemical synthesis planning, and molecular property prediction.

Drug Discovery Explainable artificial intelligence +3

BioNavi-NP: Biosynthesis Navigator for Natural Products

no code implementations26 May 2021 Shuangjia Zheng, Tao Zeng, Chengtao Li, Binghong Chen, Connor W. Coley, Yuedong Yang, Ruibo Wu

Nature, a synthetic master, creates more than 300, 000 natural products (NPs) which are the major constituents of FDA-proved drugs owing to the vast chemical space of NPs.


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