Research Articles
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.
Deep Learning for Protein Representation Encoding: From Sequence to Structure in Computational Biology
Protein representation learning (PRL) has emerged as a transformative force in computational biology, enabling data-driven insights into protein structure and function.
From Sequence to Therapy: Decoding Protein Structure-Function Relationships for Advanced Research and Drug Development
This article provides a comprehensive analysis of the protein sequence-structure-function relationship, a cornerstone of molecular biology with critical implications for biomedical research and therapeutic discovery.
Protein Language Models: How Transformer Architectures Are Revolutionizing Drug Discovery and Bioinformatics
This article provides a comprehensive overview of Protein Language Models (PLMs), deep learning systems based on Transformer architectures that are transforming computational biology and drug discovery.
Geometric Deep Learning for Protein Structures: A New Paradigm in Drug Discovery and Protein Design
This article provides a comprehensive exploration of geometric deep learning (GDL) and its transformative impact on computational biology, specifically for analyzing and designing protein structures.
Rational Protein Design and Site-Directed Mutagenesis: A Modern Guide for Researchers
This article provides a comprehensive overview of rational protein design, with a specific focus on the pivotal role of site-directed mutagenesis (SDM).
Semi-Rational Protein Design: Bridging Computational Modeling and Experimental Science for Next-Generation Therapeutics
This article provides a comprehensive overview of semi-rational protein design, a powerful methodology that synergistically combines computational modeling with experimental screening to engineer proteins with novel or enhanced functions.
Self-Supervised Learning for Protein Data: A Comprehensive Guide for Biomedical Research and Drug Discovery
This article provides a comprehensive exploration of self-supervised learning (SSL) methodologies applied to protein data, a transformative approach addressing the critical challenge of limited labeled data in computational biology.
Directed Evolution Enzyme Engineering: Protocols, Machine Learning Advances, and Biomedical Applications
This article provides a comprehensive guide to directed evolution for enzyme engineering, tailored for researchers, scientists, and drug development professionals.
Unlocking Protein Function: A Guide to Hidden Representations in Protein Sequence Space
This article explores the transformative role of hidden representations in protein sequence space, a frontier where machine learning deciphers the complex language of proteins.