Using heterogeneous Graph Neural Networks(hGNN) to predict cell-cell communication

Using heterogeneous Graph Neural Networks(hGNN) to predict cell-cell communication

This thesis investigates diverse computational methodologies for modeling cellular interactions using single-cell RNA sequencing (scRNA-seq) data. We evaluate the performance of Graph Neural Networks (GNNs) both with and without gene-gene edges, Contrastive Learning, and Variational Autoencoders (VA...

Full description

Bibliographic Details
Main Author:	Yan, Binwei
Other Authors:	Kellis, Manolis
Format:	Thesis
Published:	Massachusetts Institute of Technology 2024
Online Access:	https://hdl.handle.net/1721.1/156766

Similar Items

Explainable GNN-based models over knowledge graphs
by: Tena Cucala, DJ, et al.
Published: (2022)

CiGNN: a causality-informed and graph neural network based framework for cuffless continuous blood pressure estimation
by: Liu, L, et al.
Published: (2024)

Semantic interpretation and validation of graph attention-based explanations for GNN models
by: Panagiotaki, E, et al.
Published: (2024)

INDIGO: GNN-based inductive knowledge graph completion using pair-wise encoding
by: Liu, S, et al.
Published: (2021)

ProAffinity-GNN: a novel approach to structure-based protein-protein binding affinity prediction via a curated data set and graph neural networks
by: Zhou, Zhiyuan, et al.
Published: (2025)

Dynamic spectrum access for Internet-of-Things with joint GNN and DQN
by: Li, Feng, et al.
Published: (2024)

Contrastive learning for heterogeneous graph neural networks
by: Dong, Renzhi
Published: (2023)

Attention graph neural network on heterogeneous information network
by: Wang, Kexin
Published: (2020)

Multi-context enhanced lane-changing prediction using a heterogeneous graph neural network
by: Dong, Yiqing, et al.
Published: (2025)

A Graph Neural Network Approach for Product Relationship Prediction
by: Ahmed, Faez, et al.
Published: (2023)

Deep graph neural networks for link prediction
by: Zheng, MingXi
Published: (2024)

Power Failure Cascade Prediction using Graph Neural Networks
by: Chadaga, Sathwik, et al.
Published: (2024)

Heterogeneous graph attention network
by: Wang, Zhixing
Published: (2020)

Federated learning for graph neural networks
by: Yan, Yige
Published: (2023)

Solving aspect-based sentiment analysis task with GNN models and tree reconstruction methods
by: Peng, Cheng
Published: (2022)

Predictive neural motion planner for autonomous driving using graph networks
by: Mo, Xiaoyu, et al.
Published: (2024)

Rapid prediction of protein natural frequencies using graph neural networks
by: Guo, Kai, et al.
Published: (2022)

Graph neural network with knowledge graph
by: Ang, Qi Xuan
Published: (2020)

Prediction of Cell-Penetrating Peptides Using Artificial Neural Networks.
by: Dobchev, D, et al.
Published: (2010)

Pre-training graph neural networks for link prediction in biomedical networks
by: Long, Yahui, et al.
Published: (2022)

Graph neural networks
by: Lian, Ran
Published: (2023)

Multi-agent trajectory prediction with heterogeneous edge-enhanced graph attention network
by: Mo, Xiaoyu, et al.
Published: (2022)

Evaluating the use of graph neural networks and transfer learning for oral bioavailability prediction
by: Ng, Sherwin S. S., et al.
Published: (2023)

Map-adaptive multimodal trajectory prediction using hierarchical graph neural networks
by: Mo, Xiaoyu, et al.
Published: (2023)

Deep learning with knowledge graphs using graph neural networks
by: Liu, S
Published: (2024)

Intelligent resource allocation in joint radar-communication with graph neural networks
by: Lee, Joash, et al.
Published: (2023)

HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic
by: Liu, Shuncheng, et al.
Published: (2022)

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
by: Yang, Y, et al.
Published: (2021)

Road crash injury severity prediction using a graph neural network framework
by: Sattar, Karim A., et al.
Published: (2024)

Graph neural networks for network analysis
by: He, Y
Published: (2024)

A graph-convolutional neural network model for the prediction of chemical reactivity
by: Coley, Connor W., et al.
Published: (2022)

A graph-convolutional neural network model for the prediction of chemical reactivity
by: Coley, Connor W, et al.
Published: (2021)

Federated graph neural network
by: Koh, Tat You @ Arthur
Published: (2021)

Graph neural networks with a distribution of parametrized graphs
by: Lee, See Hian, et al.
Published: (2024)

Optimizing Graph Neural Network Training on Large Graphs
by: Stathas, Nickolas
Published: (2022)

Graph attention networks and approximate personalized propagation of neural prediction models for unsupervised graph representation learning
by: Bharadwaja, Tanay
Published: (2022)

SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
by: Zhuang, Dingyi, et al.
Published: (2024)

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
by: Xie, Tian, et al.
Published: (2018)

Graph neural network in recommender systems
by: Koh, Yi Kun
Published: (2024)

Graph neural network for anomaly detection
by: Yeo, Ming Hong
Published: (2024)