Results 61 to 70 of about 14,133 (217)
Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
Epilepsia Open, EarlyView.Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus +7 more
wiley +1 more source
Possibilities and Challenges of Using Educational Cheminformatics for STEM Education : A SWOT Analysis of a Molecular Visualization Engineering Project [PDF]
, 2022 This perspective paper analyses the possibilities and challenges of using cheminformatics as a context for STEM education. The objective is to produce theoretical insights through a SWOT analysis of an authentic educational cheminformatics project where ...
Pernaa, Johannes, Johannes Pernaa
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Journal of Applied Toxicology, EarlyView.ABSTRACT Carcinogenicity evaluation is a critical component of chemical risk assessment, yet traditional in vivo testing remains time consuming, costly, and ethically challenging. Computational approaches based on machine learning offer promising alternatives, but the relative contributions of different molecular representation strategies for ...
Iuri Barbosa Pereira +2 more
wiley +1 more source
Medicinal Research Reviews, EarlyView.ABSTRACT Natural products (NPs) have historically yielded numerous therapeutic agents, yet their integration into modern drug discovery has been constrained by chemical complexity, low abundance, laborious dereplication, and limited target annotation.
Antonio Lavecchia
wiley +1 more source
Application of Transformers in Cheminformatics
Journal of Chemical Information and ModelingBy accelerating time-consuming processes with high efficiency, computing has become an essential part of many modern chemical pipelines. Machine learning is a class of computing methods that can discover patterns within chemical data and utilize this knowledge for a wide variety of downstream tasks, such as property prediction or substance generation ...
Kha-Dinh Luong, Ambuj K. Singh
openaire +2 more sources
Journal of Cheminformatics - Volume 3
, 2013 Collection of all CC-BY-licensed Volume 3 papers from the Journal of Cheminformatics.
Egon Willighagen (96390)
core +1 more source
ChemInformatics Model Explorer (CIME): Exploratory analysis of chemical model explanations
, 2023 Datasets used in the use cases of the article: ChemInformatics Model Explorer (CIME): Exploratory analysis of chemical model ...
Florian Huber +7 more
core +1 more source
Materials Genome Engineering Advances, EarlyView.A sequence‐sensitive multi‐fidelity hybrid modeling framework combined with a teacher‐student genetic algorithm enables the inverse design of copolyamides. The hybrid model balances prediction accuracy, sequence‑sensitivity, and computational cost. A two‑tier genetic algorithm can efficiently identify the monomer structures and ratios of copolyamides ...
Sheng Chen +8 more
wiley +1 more source
<h2><a href="https://github.com/Steinbeck-Lab/cheminformatics-microservice/compare/v2.0.0...v2.1.0">2.1.0</a> (2024-01-11)</h2> <h3>Features</h3> <ul> <li>Add ertl functional groups and test (<a href ...
Sharma, Nisha +4 more
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CHEMINFORMATICS: AN INTRODUCTION
, 2018 Cheminformatics is an interdisciplinary field between chemistry and informatics, which has evolved considerably since its inception in the 1960s. Initially, the cheminformatics community dealt primarily with practical and technical aspects of chemical ...
Carolina Horta Andrade (2820991) +3 more
core +1 more source