This article provides a detailed exploration of active learning (AL) strategies for optimizing virtual screening (VS) in early-stage drug discovery.
This article provides a comprehensive framework for researchers and drug development professionals aiming to assess the accuracy of real-world treatment regimens derived from electronic health records (EHR).
This article provides a detailed exploration and accuracy assessment of hybrid methodologies that combine deep learning architectures with metaheuristic algorithms for high-dimensional gene selection in biomedical research.
This article explores the Waddington epigenetic landscape as a foundational framework for understanding and inducing cancer reversion.
This article provides a detailed exploration of the SHAFTS (SHApe-FeaTure Similarity) method for 3D molecular similarity searching in virtual screening.
This article explores RNA interference (RNAi) as a powerful, reversible, and non-mutagenic approach to cancer reversion.
This article provides researchers, scientists, and drug development professionals with a comprehensive framework for utilizing Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) analyses to validate the...
This article provides a detailed examination of the RECIST (Response Evaluation Criteria In Solid Tumors) 1.1 framework for evaluating tumor response in clinical trials of targeted cancer therapies.
This article provides a comprehensive guide to the Ranked Biomarker and Noise Reduction Optimization with Differential Evolution (RBNRO-DE) algorithm for gene selection in high-dimensional biological data.
This article provides a detailed exploration of Pharmacokinetic/Pharmacodynamic (PK/PD) modeling as a cornerstone of modern oncology drug development and personalized treatment.