Research Articles
Advancing Anticancer Drug Discovery: A Comprehensive Guide to PLK1 Inhibitor Development Using 3D-QSAR Models
This article provides a comprehensive resource for researchers and drug development professionals exploring Polo-like kinase 1 (PLK1) inhibitors through 3D-QSAR modeling.
Molecular Alignment in 3D-QSAR: Advanced Techniques for Accelerating Anticancer Drug Discovery
This article provides a comprehensive exploration of molecular alignment techniques, a critical and sensitive step in developing robust three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) models for anticancer research.
CoMFA and CoMSIA in Cancer Research: A Comprehensive Guide to 3D-QSAR Drug Design
This article provides a comprehensive overview of Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA), two pivotal 3D-QSAR techniques revolutionizing computer-aided anticancer drug discovery.
How 3D-QSAR Predicts Anticancer Compound Activity: A Computational Guide for Drug Discovery
This article provides a comprehensive overview of the application of 3D Quantitative Structure-Activity Relationship (3D-QSAR) modeling in predicting the activity of anticancer compounds.
Comprehensive Validation of Anticancer Compounds: A Guide to MCF-7 Cell Line In Vitro Assays
This article provides a comprehensive guide for researchers and drug development professionals on the validation of anticancer compounds using the MCF-7 breast cancer cell line.
Medical Image Denoising: A Comprehensive Guide to Techniques, Validation, and Clinical Application for Researchers
This article provides a comprehensive analysis of data denoising techniques for medical images, tailored for researchers, scientists, and drug development professionals.
Machine Learning vs. Deep Learning for Cancer Detection: A Comparative Analysis for Researchers and Drug Developers
This article provides a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) methodologies for cancer detection, tailored for researchers, scientists, and drug development professionals.
External Validation of Cancer Risk Prediction Algorithms: A Foundational Guide for Biomedical Research and Clinical Translation
This article provides a comprehensive overview of the critical role of external validation in the development and implementation of cancer risk prediction algorithms.
Mitigating Overfitting in Cancer Detection Models: Strategies for Robust and Generalizable AI
This article provides a comprehensive analysis of overfitting, a critical challenge that compromises the generalizability and clinical reliability of deep learning models in cancer detection.
Advanced Feature Selection Methods for High-Dimensional Oncology Data: From Foundations to Clinical Applications
This article provides a comprehensive guide to feature selection techniques tailored for high-dimensional oncology data, such as gene expression, DNA methylation, and multi-omics datasets.