Awesome q-bio.MN

Modularity Emerges from Action-Functional Constraints in Marine Metabolic Networks: A Biology-Scale Validation of the Network-Weighted Action Principle (2026)

Martin G. Frasch

1.83

PACER: Acyclic Causal Discovery from Large-Scale Interventional Data (2026)

Ramon Vi\~nas Torn\'e et al.

1.83

Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks (2026)

Kyle Higgins et al.

1.83

CMGL: Confidence-guided Multi-omics Graph Learning for Cancer Subtype Classification (2026)

Boyang Fan et al.

1.78

RAG-GNN: Integrating Retrieved Knowledge with Graph Neural Networks for Precision Medicine (2026)

Hasi Hays and William J. Richardson

1.67

Complex Networks and the Drug Repositioning Problem (2026)

Felipe Bivort Haiek

1.67

PLANET v2.0: A comprehensive Protein-Ligand Affinity Prediction Model Based on Mixture Density Network (2026)

Haotian Gao et al.

1.61

Hierarchical Molecular Language Models (HMLMs) (2025)

Hasi Hays et al.

1.56

Gene regulatory network inference algorithm based on spectral signed directed graph convolution (2025)

Rijie Xi et al.

1.56

Biological Regulatory Network Inference through Circular Causal Structure Learning (2025)

Hongyang Jiang et al.

1.50

SPECTRA: Spectral Domain-Aware Graph Generation for Imbalanced Molecular Property Regression (2025)

Brenda Nogueira et al.

1.50

Practical Causal Evaluation Metrics for Biological Networks (2025)

Noriaki Sato and Marco Scutari and Shuichi Kawano and Rui Yamaguchi and Seiya Imoto

1.50

ProtoMol: Enhancing Molecular Property Prediction via Prototype-Guided Multimodal Learning (2025)

Yingxu Wang et al.

1.44

Biological Pathway Informed Models with Graph Attention Networks (GATs) (2025)

Gavin Wong et al.

1.39

Modeling GRNs with a Probabilistic Categorical Framework (2025)

Yiyang Jia et al.

1.33

Spectral Manifold Harmonization for Graph Imbalanced Regression (2025)

Brenda Nogueira et al.

1.28

PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs (2025)

Xinzhe Zheng et al.

1.28

Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations (2025)

Mengjie Chen et al.

1.28

Symmetries of weighted networks: weight approximation method and its application to food webs (2025)

Julia Korol et al.

1.22

Evolutionary chemical learning in dimerization networks (2025)

Alexei V. Tkachenko et al.

1.22

Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks - the GATTACA Framework (2025)

Andrzej Mizera et al.

1.17

Bidirectional Hierarchical Protein Multi-Modal Representation Learning (2025)

Xuefeng Liu et al.

1.11

A Novel Graph Transformer Framework for Gene Regulatory Network Inference (2025)

Binon Teji and Swarup Roy

1.11

The Signed Two-Space Proximity Model for Learning Representations in Protein-Protein Interaction Networks (2025)

Nikolaos Nakis and Chrysoula Kosma and Anastasia Brativnyk and Michail Chatzianastasis and Iakovos Evdaimon and Michalis Vazirgiannis

1.06

Pangraphs as models of higher-order interactions (2025)

Mateusz Iskrzy\'nski et al.

1.00

Finding Influential Cores via Normalized Ricci Flows in Directed and Undirected Hypergraphs with Applications (2025)

Prithviraj Sengupta et al.

1.00

Benchmarking Constraint-Based Bayesian Structure Learning Algorithms: Role of Network Topology (2025)

Radha Nagarajan et al.

0.94

Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations (2025)

Zaikang Lin et al.

0.94

A Hybrid Supervised and Self-Supervised Graph Neural Network for Edge-Centric Applications (2025)

Eugenio Borzone et al.

0.94

Translating and evaluating single-cell Boolean network interventions in the multiscale setting (2025)

John Metzcar et al.

0.94

Identifying efficient controls of complex interaction networks using genetic algorithms (2020)

Victor-Bogdan Popescu and Krishna Kanhaiya and Iulian N\u{a}stac and Eugen Czeizler and Ion Petre

—

Learning Heat Diffusion for Network Alignment (2020)

Sisi Qu et al.

—

EPGAT: Gene Essentiality Prediction With Graph Attention Networks (2020)

Jo\~ao Schapke et al.

—

Graphical Conditions for Rate Independence in Chemical Reaction Networks (2020)

Elisabeth Degrand (Lifeware) et al.

—

MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach (2020)

L\'eo Pio-Lopez et al.

—

TaBooN -- Boolean Network Synthesis Based on Tabu Search (2020)

Sara Sadat Aghamiri et al.

—

Dr-COVID: Graph Neural Networks for SARS-CoV-2 Drug Repurposing (2020)

Siddhant Doshi and Sundeep Prabhakar Chepuri

—

An algebraic approach to product-form stationary distributions for some reaction networks (2020)

Beatriz Pascual-Escudero and Linard Hoessly

—

Geometric algorithms for sampling the flux space of metabolic networks (2020)

Apostolos Chalkis (NKUA et al.

—

An algorithm for network community structure determination by surprise (2020)

Daniel Gamermann et al.

—

Complex network prediction using deep learning (2021)

Yoshihisa Tanaka et al.

—

Graph Representation Learning in Biomedicine (2021)

Michelle M. Li et al.

—

Deep Contextual Learners for Protein Networks (2021)

Michelle M. Li et al.

—

ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction (2021)

Xiaomin Fang et al.

—

Universal Multilayer Network Exploration by Random Walk with Restart (2021)

Anthony Baptista et al.

—

Structural characteristics in network control of molecular multiplex networks (2021)

Cheng Yuan et al.

—

BioCode: A Data-Driven Procedure to Learn the Growth of Biological Networks (2021)

Emre Sefer

—

Graph-guided random forest for gene set selection (2021)

Bastian Pfeifer et al.

—

Inferring gene regulation dynamics from static snapshots of gene expression variability (2021)

Euan Joly-Smith et al.

—

RNAglib: A Python Package for RNA 2.5D Graphs (2021)

Vincent Mallet et al.

—

Neural Upscaling from Residue-level Protein Structure Networks to Atomistic Structure (2021)

Vy Duong et al.

—

Accurately Modeling Biased Random Walks on Weighted Graphs Using $\textit{Node2vec+}$ (2021)

Renming Liu et al.

—

Network Refinement: A unified framework for enhancing signal or removing noise of networks (2021)

Jiating Yu et al.

—

Understanding the network formation pattern for better link prediction (2021)

Jiating Yu and Ling-Yun Wu

—

On the feasibility of dynamical analysis of network models of biochemical regulation (2021)

Luis M. Rocha

—

Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs (2021)

Stephen Bonner et al.

—

HampDTI: a heterogeneous graph automatic meta-path learning method for drug-target interaction prediction (2021)

Hongzhun Wang et al.

—

DeepAutoPIN: An automorphism orbits based deep neural network for characterizing the organizational diversity of protein interactomes across the tree of life (2022)

Vikram Singh and Vikram Singh

—

A Survey on Deep Graph Generation: Methods and Applications (2022)

Yanqiao Zhu and Yuanqi Du and Yinkai Wang and Yichen Xu and Jieyu Zhang and Qiang Liu and Shu Wu

—

Spatiotemporal Patterns in Neurobiology: An Overview for Future Artificial Intelligence (2022)

Sean Knight et al.

—

Awesome q-bio.MN

Datasets & benchmarks

Key papers

q-bio.MN

Awesome q-bio.MN

Datasets & benchmarks

Key papers