Research Articles
Beyond Sequence Alignment: How Physicochemical Property Analysis is Revolutionizing Protein Comparison and Drug Discovery
This article provides a comprehensive guide to alignment-free protein sequence comparison using physicochemical properties.
Beyond the Training Set: Mastering Dataset Shift for Accurate Protein-Ligand Interaction Prediction
This article addresses the critical challenge of dataset shift in machine learning models for protein-ligand interaction (PLI) prediction, a major bottleneck in AI-driven drug discovery.
Beyond the Training Set: Confronting Dataset Bias in Protein Language Models for Robust Drug Discovery
This article provides a comprehensive guide for researchers and drug development professionals on identifying, mitigating, and evaluating dataset bias in protein representation learning.
The Invisible Hand: Identifying, Understanding, and Mitigating Annotation Bias in Protein AI Training Data
Protein machine learning models are revolutionizing drug discovery and functional prediction, but their performance is fundamentally limited by the quality and bias inherent in their training data.
From Sequence to Structure: A 2024 Review of AI-Driven De Novo Protein Design
This comprehensive review explores the transformative impact of artificial intelligence on de novo protein design, a field moving beyond natural evolution to create novel proteins with customized functions.
AI-Designed Protein Cages: Revolutionizing Nanomedicine from Drug Delivery to Vaccines
This comprehensive article explores the frontier of AI-designed protein cage nanomaterials, detailing their foundational principles, innovative design methodologies, and transformative biomedical applications.
From Sequence to Therapy: How AI is Revolutionizing Protein Binder Design for Next-Generation Therapeutics
This article provides a comprehensive overview of AI-driven protein binder design for therapeutic applications.
From Sequence to Cure: How AI and Machine Learning Are Revolutionizing Protein Therapeutic Discovery
This article provides a comprehensive overview of the transformative role of artificial intelligence (AI) and machine learning (ML) in protein therapeutic discovery.
From Sequence to Structure: The Power of 3D Geometric Representations in Protein Research and Drug Discovery
This article provides a comprehensive guide to 3D geometric representations of protein sequences for researchers and drug development professionals.
Overcoming Data Scarcity in Protein Engineering: AI-Driven Strategies for Success with Limited Experimental Data
This article provides researchers, scientists, and drug development professionals with a comprehensive framework for advancing protein engineering projects when experimental data is scarce.