This article provides a comprehensive framework for researchers, scientists, and drug development professionals to evaluate keyword recommendation systems that utilize hierarchical controlled vocabularies.
This article provides a comprehensive analysis of 2D and 3D molecular representation learning for property prediction, a critical task in modern drug discovery and materials science.
This article provides a comprehensive guide to controlled vocabulary annotation for researchers, scientists, and drug development professionals.
This article provides a comprehensive framework for developing robust research hypotheses in materials science and drug development through inductive theorizing.
This article provides a comprehensive overview of foundation models (FMs) and their transformative impact on materials discovery.
This article provides a comprehensive, comparative analysis of machine learning (ML) algorithms for predicting material properties, a critical task in accelerating material discovery and design.
This article provides a comprehensive framework for the cost-performance validation of computationally predicted bimetallic catalysts, addressing a critical gap between theoretical design and practical application.
This article provides a comprehensive framework for validating the stability predictions of Heusler compounds against experimental data, a critical step for their application in functional materials.
This article provides a comprehensive analysis of the performance of various functionalized Metal-Organic Frameworks (MOFs) for carbon dioxide capture, addressing key considerations for researchers and scientists.
This article provides a critical analysis of experimental piezoelectric constants for organic crystals, serving as a benchmark for researchers and scientists developing materials for biomedical and energy applications.