Cover Image

CBINNS: Cancer Biology-Informed Neural Network for Unknown Parameter Estimation and Missing Physics Identification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chhetri, Bishal, Kumar, B. V. Rathish
Format:	Preprint
Published:	2025
Subjects:	Quantitative Methods Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Variational and Explanatory Neural Networks for Encoding Cancer Profiles and Predicting Drug Responses
by: Feng, Tianshu, et al.
Published: (2024)

Bridging Accuracy and Interpretability: Deep Learning with XAI for Breast Cancer Detection
by: Chhetri, Bishal, et al.
Published: (2025)

Discovering intrinsic multi-compartment pharmacometric models using Physics Informed Neural Networks
by: Nasim, Imran, et al.
Published: (2024)

Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction
by: Mojarrad, Fatemeh Nassajian, et al.
Published: (2024)

Do Biological Structural Guarantees Earn Their Complexity?
by: Banu, Bogdan
Published: (2026)

Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization
by: Wu, Lirong, et al.
Published: (2024)

Biomarker Discovery with Quantum Neural Networks: A Case-study in CTLA4-Activation Pathways
by: Nguyen, Nam
Published: (2023)

Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning
by: Caranzano, Isabella, et al.
Published: (2025)

Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins
by: Sinclair, Matthew, et al.
Published: (2025)

BixBench: a Comprehensive Benchmark for LLM-based Agents in Computational Biology
by: Mitchener, Ludovico, et al.
Published: (2025)

Can Large Language Models Design Biological Weapons? Evaluating Moremi Bio
by: Hattoh, Gertrude, et al.
Published: (2025)

Literature Mining System for Nutraceutical Biosynthesis: From AI Framework to Biological Insight
by: Sun, Xinyang, et al.
Published: (2025)

A Multimodal Foundation Model of Spatial Transcriptomics and Histology for Biological Discovery and Clinical Prediction
by: Xiang, Jinxi, et al.
Published: (2026)

BioArc: Discovering Optimal Neural Architectures for Biological Foundation Models
by: Fang, Yi, et al.
Published: (2025)

From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research
by: Muneer, Amgad, et al.
Published: (2025)

Physics-Informed Machine Learning in Biomedical Science and Engineering
by: Ahmadi, Nazanin, et al.
Published: (2025)

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences
by: Yan, Zhanglu, et al.
Published: (2024)

Predicting Survivability of Cancer Patients with Metastatic Patterns Using Explainable AI
by: Nalela, Polycarp, et al.
Published: (2025)

Revolutionizing Personalized Cancer Vaccines with NEO: Novel Epitope Optimization Using an Aggregated Feed Forward and Recurrent Neural Network with LSTM Architecture
by: Basava, Nishanth
Published: (2024)

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation
by: Liu, Xinyi, et al.
Published: (2025)

Contextual Invertible World Models: A Neuro-Symbolic Agentic Framework for Colorectal Cancer Drug Response
by: Baker, Christopher, et al.
Published: (2026)

Mamba-SSM with LLM Reasoning for Feature Selection: Faithfulness-Aware Biomarker Discovery
by: Balan, Pushpa Kumar, et al.
Published: (2026)

Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
by: Deng, Alana, et al.
Published: (2026)

GAN-TAT: A Novel Framework Using Protein Interaction Networks in Druggable Gene Identification
by: Wang, George Yuanji, et al.
Published: (2024)

Neural Diffusion Processes for Physically Interpretable Survival Prediction
by: Cristofoletto, Alessio, et al.
Published: (2025)

Physics-Informed Neural Koopman Machine for Interpretable Longitudinal Personalized Alzheimer's Disease Forecasting
by: Hrusanov, Georgi, et al.
Published: (2025)

Attention Networks for Personalized Mealtime Insulin Dosing in People with Type 1 Diabetes
by: Fathi, Anas El, et al.
Published: (2024)

Cross-Attention Graph Neural Networks for Inferring Gene Regulatory Networks with Skewed Degree Distribution
by: Xiong, Jiaqi, et al.
Published: (2024)

A Scalable Tool For Analyzing Genomic Variants Of Humans Using Knowledge Graphs and Machine Learning
by: Prasanna, Shivika, et al.
Published: (2024)

UMMAN: Unsupervised Multi-graph Merge Adversarial Network for Disease Prediction Based on Intestinal Flora
by: Liu, Dingkun, et al.
Published: (2024)

LLMs Outperform Experts on Challenging Biology Benchmarks
by: Justen, Lennart
Published: (2025)

Prostate-VarBench: A Benchmark with Interpretable TabNet Framework for Prostate Cancer Variant Classification
by: Tavara, Abraham Francisco Arellano, et al.
Published: (2025)

MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
by: Yu, Zhaoning, et al.
Published: (2024)

Empowering Chemical Structures with Biological Insights for Scalable Phenotypic Virtual Screening
by: Lian, Xiaoqing, et al.
Published: (2026)

BioMaze: Benchmarking and Enhancing Large Language Models for Biological Pathway Reasoning
by: Zhao, Haiteng, et al.
Published: (2025)

A Physiologically-Constrained Neural Network Digital Twin Framework for Replicating Glucose Dynamics in Type 1 Diabetes
by: Roquemen-Echeverri, Valentina, et al.
Published: (2025)

NaNa and MiGu: Semantic Data Augmentation Techniques to Enhance Protein Classification in Graph Neural Networks
by: Lan, Yi-Shan, et al.
Published: (2024)

Horizon-wise Learning Paradigm Promotes Gene Splicing Identification
by: Li, Qi-Jie, et al.
Published: (2024)

Cell-cell Communication Inference and Analysis: Biological Mechanisms, Computational Approaches, and Future Opportunities
by: Cheng, Xiangzheng, et al.
Published: (2025)

HyboWaveNet: Hyperbolic Graph Neural Networks with Multi-Scale Wavelet Transform for Protein-Protein Interaction Prediction
by: Yu, Qingzhi, et al.
Published: (2025)