Research Articles
Independent Validation of m6A-Related lncRNA Signatures for Predicting Overall Survival in Cancer
This article provides a comprehensive resource for researchers and drug development professionals on the independent validation of prognostic signatures based on m6A-related long non-coding RNAs (lncRNAs).
Optimizing m6A-Related lncRNA Prognostic Models: A Comprehensive Guide to Enhancing ROC Curve Performance
This article provides a comprehensive framework for researchers and bioinformaticians aiming to develop and optimize prognostic models based on m6A-related long non-coding RNAs (lncRNAs).
Controlling False Discovery Rates in m6A-Related lncRNA Signature Studies: A Guide for Robust Biomarker Development
This article provides a comprehensive guide for researchers and drug development professionals on implementing rigorous false discovery rate (FDR) control in studies of N6-methyladenosine (m6A)-related long non-coding RNA (lncRNA) signatures.
Preventing Overfitting in m6A-lncRNA Signatures: A Cross-Validation Guide for Robust Biomarker Development
This article provides a comprehensive framework for researchers and drug development professionals to construct and validate prognostic m6A-related lncRNA signatures while rigorously preventing overfitting.
m6A-Related lncRNA Signatures: Predictive Biomarkers for Immunotherapy Response in Cancer
This comprehensive review explores the emerging role of m6A-related long non-coding RNA (lncRNA) signatures as powerful prognostic tools and predictors of immunotherapy efficacy across multiple cancer types.
Benchmarking Recursive Feature Elimination (RFE) in Drug Discovery: A Practical Guide for Researchers
This article provides a comprehensive benchmark analysis of Recursive Feature Elimination (RFE) against other feature selection methods in drug discovery applications.
Filter, Wrapper, and RFE: A Practical Guide to Feature Selection in Cheminformatics
This article provides a comprehensive guide to feature selection methods for researchers and professionals in drug development.
RFE vs PCA: A Machine Learning Guide to Boost Anti-Cathepsin Prediction Accuracy
Selecting the optimal feature selection technique is critical for developing accurate and generalizable machine learning models in drug discovery.
Robust QSAR Modeling: A Guide to Handling Multicollinearity in Molecular Descriptors for Recursive Feature Elimination
Multicollinearity among molecular descriptors presents significant challenges for feature selection in QSAR modeling, particularly when using Recursive Feature Elimination (RFE).
RFE-SMOTE Pipeline: Tackling Imbalanced Data in Chemical Research and Drug Discovery
This article provides a comprehensive guide for researchers and drug development professionals on implementing a pipeline combining Recursive Feature Elimination (RFE) and the Synthetic Minority Oversampling Technique (SMOTE) to address...