Regulatory Network

Gene regulatory networks (GRNs) describe the complex interactions governing gene expression, crucial for understanding cellular processes and disease. Current research focuses on developing robust methods to infer these networks from diverse data types, including single-cell transcriptomics and perturbation experiments, employing machine learning approaches such as graph neural networks, transformers, and Bayesian methods. These advancements improve the accuracy and scalability of GRN inference, leading to better understanding of biological mechanisms and informing applications in personalized medicine and drug discovery. The field is also increasingly emphasizing causal inference and the incorporation of prior biological knowledge to enhance model interpretability and predictive power.

Papers

October 21, 2024

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation
Tejumade Afonja, Ivaxi Sheth, Ruta Binkyte, Waqar Hanif, Thomas Ulas, Matthias Becker, Mario Fritz
Large Language Model Global Evaluation Causal Discovery Synthetic Data Generation Regulatory Network Single Cell RNA scRNA Seq

October 1, 2024

Recovering Time-Varying Networks From Single-Cell Data
Euxhen Hasanaj, Barnabás Póczos, Ziv Bar-Joseph
Single Cell Temporal Network Regulatory Network Single Cell Data Time Varying Network Gene Network

September 30, 2024

Robust Multi-view Co-expression Network Inference
Teodora Pandeva, Martijs Jonker, Leendert Hamoen, Joris Mooij, Patrick Forré
Gene Expression Data Regulatory Network

September 20, 2024

Analysis of Gene Regulatory Networks from Gene Expression Using Graph Neural Networks
Hakan T. Otal, Abdulhamit Subasi, Furkan Kurt, M. Abdullah Canbaz, Yasin Uzun
Graph Neural Network General Analysis Graph Attention Network Gene Expression Data Regulatory Network

July 25, 2024

Gene Regulatory Network Inference from Pre-trained Single-Cell Transcriptomics Transformer with Joint Graph Learning
Sindhura Kommu, Yizhi Wang, Yue Wang, Xuan Wang
Transformer Language Model Pre Trained BERT Regulatory Network scRNA Seq Gene Regulatory Neural Network

July 16, 2024

A Discrete Perspective Towards the Construction of Sparse Probabilistic Boolean Networks
Christopher H. Fok, Chi-Wing Wong, Wai-Ki Ching
Many Sparse Construction Industry Regulatory Network Probabilistic Boolean Network

March 16, 2024

Identifying the Attractors of Gene Regulatory Networks from Expression Data under Uncertainty: An Interpretable Approach
Alireza Rowhanimanesh
High Uncertainty Anticipation Regulatory Network New Attractor Expression Dataset Attractor Landscape

March 7, 2024

Cell reprogramming design by transfer learning of functional transcriptional networks
Thomas P. Wytock, Adilson E. Motter
Transfer Learning Product Design Regulatory Network Entire Transcription Process Cell Center Control Behavior

February 27, 2024

Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma
Abanti Bhattacharjya, Md Manowarul Islam, Md Ashraf Uddin, Md. Alamin Talukder, AKM Azad, Sunil Aryal, Bikash Kumar Paul, Wahia Tasnim, Muhammad Ali Abdulllah Almoyad, Mohammad Ali Moni
Computational Biology Regulatory Network Genome Understanding Drug Molecule Nasopharyngeal Carcinoma Genetic Network Lung Adenocarcinoma

January 14, 2024

Inference of dynamical gene regulatory networks from single-cell data with physics informed neural networks
Maria Mircea, Diego Garlaschelli, Stefan Semrau
Neural Network Physic Informed Neural Network Scientific Inference Regulatory Network Single Cell Data Mechanistic Understanding Dynamical Evolution

October 29, 2023

Gauge-optimal approximate learning for small data classification problems
Edoardo Vecchi, Davide Bassetti, Fabio Graziato, Lukas Pospisil, Illia Horenko
Computational Biology Regulatory Network Dimensional Space Small Training

October 5, 2023

Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems
Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu
Large Scale Causal Inference Causal Discovery Potential Scalability Causal Structure Regulatory Network SWIFT DynGFN

September 21, 2023

Boolformer: Symbolic Regression of Logic Functions with Transformers
Stéphane d'Ascoli, Samy Bengio, Josh Susskind, Emmanuel Abbé
Transformer Megatron Decepticons Symbolic Regression Binary Classification Regulatory Network Boolean Function

September 14, 2023

Stability Analysis of Non-Linear Classifiers using Gene Regulatory Neural Network for Biological AI
Adrian Ratwatte, Samitha Somathilaka, Sasitharan Balasubramaniam, Assaf A. Gilad
Stability Analysis Non Linear Regulatory Network Reaction Network Elementary Perceptron Biological Intelligence Gene Regulatory Neural Network

June 13, 2023

Inferring dynamic regulatory interaction graphs from time series data with perturbations
Dhananjay Bhaskar, Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy
Time Series Data Additive Perturbation Regulatory Network Interaction Graph Time Varying Graph Gene Regulatory Neural Network

May 30, 2023

dotears: Scalable, consistent DAG estimation using observational and interventional data
Albert Xue, Jingyou Rao, Sriram Sankararaman, Harold Pimentel
Potential Scalability Causal Structure Causal Direction Score Based Dot Product Regulatory Network DAG Learning Interventional Data

April 25, 2023

CIMLA: Interpretable AI for inference of differential causal networks
Payam Dibaeinia, Saurabh Sinha
Scientific Inference Causal Relationship Single Cell Feature Attribution Method Interpretable AI Regulatory Network Causal Interpretation

April 12, 2023

DiscoGen: Learning to Discover Gene Regulatory Networks
Nan Rosemary Ke, Sara-Jane Dunn, Jorg Bornschein, Silvia Chiappa, Melanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane Wang, Theophane Weber, David Barrett, Matthew Botvinick, Anirudh Goyal, Mike Mozer, Danilo Rezende
Causal Discovery Causal Discovery Method Regulatory Network Genetic Network

April 11, 2023

Biological Factor Regulatory Neural Network
Xinnan Dai, Caihua Shan, Jie Zheng, Xiaoxiao Li, Dongsheng Li
Biological Neural Network Gene Expression Data Regulatory Network Protein Interaction Network

March 8, 2023

Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level
Chase Yakaboski, Eugene Santos
Strong Generalization Bayesian Network Probabilistic Graphical Model Regulatory Network Bayesian Structure Instantiation Based

Regulatory Network

Papers

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation

Recovering Time-Varying Networks From Single-Cell Data

Robust Multi-view Co-expression Network Inference

Analysis of Gene Regulatory Networks from Gene Expression Using Graph Neural Networks

Gene Regulatory Network Inference from Pre-trained Single-Cell Transcriptomics Transformer with Joint Graph Learning

A Discrete Perspective Towards the Construction of Sparse Probabilistic Boolean Networks

Identifying the Attractors of Gene Regulatory Networks from Expression Data under Uncertainty: An Interpretable Approach

Cell reprogramming design by transfer learning of functional transcriptional networks

Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma

Inference of dynamical gene regulatory networks from single-cell data with physics informed neural networks

Gauge-optimal approximate learning for small data classification problems

Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems

Boolformer: Symbolic Regression of Logic Functions with Transformers

Stability Analysis of Non-Linear Classifiers using Gene Regulatory Neural Network for Biological AI

Inferring dynamic regulatory interaction graphs from time series data with perturbations

dotears: Scalable, consistent DAG estimation using observational and interventional data

CIMLA: Interpretable AI for inference of differential causal networks

DiscoGen: Learning to Discover Gene Regulatory Networks

Biological Factor Regulatory Neural Network

Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level