Cover Image

Causal Cellular Context Transfer Learning (C3TL): An Efficient Architecture for Prediction of Unseen Perturbation Effects

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Scholkemper, Michael, Mukherjee, Sach
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Identifiable Factorized Causal Representations of Cellular Responses
by: Mao, Haiyi, et al.
Published: (2024)

Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
by: Bereket, Michael, et al.
Published: (2023)

Dual-Pathway Fusion of EHRs and Knowledge Graphs for Predicting Unseen Drug-Drug Interactions
by: Lee, Franklin, et al.
Published: (2025)

Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction
by: Maleki, Sepideh, et al.
Published: (2024)

Learning Causally Predictable Outcomes from Psychiatric Longitudinal Data
by: Strobl, Eric V.
Published: (2025)

Efficient Data Selection for Training Genomic Perturbation Models
by: Panagopoulos, George, et al.
Published: (2025)

TxPert: Leveraging Biochemical Relationships for Out-of-Distribution Transcriptomic Perturbation Prediction
by: Wenkel, Frederik, et al.
Published: (2025)

Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schrödinger Bridges
by: Chi, Changxi, et al.
Published: (2025)

ADEP: A Novel Approach Based on Discriminator-Enhanced Encoder-Decoder Architecture for Accurate Prediction of Adverse Effects in Polypharmacy
by: Kobraei, Katayoun, et al.
Published: (2024)

Deep Neural Cellular Potts Models
by: Minartz, Koen, et al.
Published: (2025)

Interpretable Causal Representation Learning for Biological Data in the Pathway Space
by: de la Fuente, Jesus, et al.
Published: (2025)

HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference
by: Zang, Zelin, et al.
Published: (2025)

Knowledge from Large-Scale Protein Contact Prediction Models Can Be Transferred to the Data-Scarce RNA Contact Prediction Task
by: Jian, Yiren, et al.
Published: (2023)

No Generation without Representation: Efficient Causal Protein Language Models Enable Zero-Shot Fitness Estimation
by: Eris, Furkan
Published: (2026)

Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms
by: Ota, Nobuyuki
Published: (2026)

Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
by: Xu, Kaichen, et al.
Published: (2025)

BioBO: Biology-informed Bayesian Optimization for Perturbation Design
by: Li, Yanke, et al.
Published: (2025)

Protenix-Mini: Efficient Structure Predictor via Compact Architecture, Few-Step Diffusion and Switchable pLM
by: Gong, Chengyue, et al.
Published: (2025)

Predicting Activity Cliffs for Autonomous Medicinal Chemistry
by: Cuccarese, Michael
Published: (2026)

AROMA: Augmented Reasoning Over a Multimodal Architecture for Virtual Cell Genetic Perturbation Modeling
by: Wang, Zhenyu, et al.
Published: (2026)

pAE: An Efficient Autoencoder Architecture for Modeling the Lateral Geniculate Nucleus by Integrating Feedforward and Feedback Streams in Human Visual System
by: Gorji, Moslem, et al.
Published: (2024)

A Causal Framework for Precision Rehabilitation
by: Cotton, R. James, et al.
Published: (2024)

Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays
by: Sedgwick, Ruby, et al.
Published: (2024)

Predicting Side Effect of Drug Molecules using Recurrent Neural Networks
by: Beaudoin, Collin, et al.
Published: (2023)

Effect of Clinical History on Predictive Model Performance for Renal Complications of Diabetes
by: Cas, Davide Dei, et al.
Published: (2024)

Causal Representation Learning from Multimodal Biomedical Observations
by: Sun, Yuewen, et al.
Published: (2024)

Dual-Modality Representation Learning for Molecular Property Prediction
by: Zhao, Anyin, et al.
Published: (2025)

Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
by: Guo, Peijin, et al.
Published: (2025)

Efficient and Robust Continual Graph Learning for Graph Classification in Biology
by: Zhang, Ding, et al.
Published: (2024)

Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data
by: Zahoor, Sheresh, et al.
Published: (2025)

A Graph-in-Graph Learning Framework for Drug-Target Interaction Prediction
by: Song, Yuehua, et al.
Published: (2025)

Virtual Cells: Predict, Explain, Discover
by: Noutahi, Emmanuel, et al.
Published: (2025)

Escaping Local Optima in the Waddington Landscape: A Two-Stage TRPO-PPO Approach for Single-Cell Perturbation Analysis
by: Boabang, Francis, et al.
Published: (2025)

Causal Inference, Biomarker Discovery, Graph Neural Network, Feature Selection
by: Lan, Chaowang, et al.
Published: (2025)

Deep Reinforcement Learning for Controlled Traversing of the Attractor Landscape of Boolean Models in the Context of Cellular Reprogramming
by: Mizera, Andrzej, et al.
Published: (2024)

Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review
by: Vefghi, Ali, et al.
Published: (2025)

Blood Glucose Level Prediction in Type 1 Diabetes Using Machine Learning
by: Chu, Soon Jynn, et al.
Published: (2025)

STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics
by: Rocha, Joao F., et al.
Published: (2025)

Multimodal Machine Learning for Early Prediction of Metastasis in a Swedish Multi-Cancer Cohort
by: Rugolon, Franco, et al.
Published: (2026)

HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction
by: Liu, Bin, et al.
Published: (2024)