Results 41 to 50 of about 21,290 (203)
The benefits of in silico modeling to identify possible small-molecule drugs and their off-target interactions [PDF]
, 2018 Accepted for publication in a future issue of Future Medicinal Chemistry.The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative ...
Blomberg N +6 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
Molecules, 2019 Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. Since numerous beneficial applications of phenols as preventive agents in various diseases were revealed, the evaluation of phenols bioavailability is of high
Katja Venko, Marjana Novič
doaj +1 more source
Molecules, 2021 Background: The growing demand for agricultural products has led to the misuse/overuse of insecticides; resulting in the use of higher concentrations and the need for ever more toxic products. Ecologically, bioinsecticides are considered better and safer
Gabriela Cristina Soares Rodrigues +5 more
doaj +1 more source
HyperLoom: A platform for defining and executing scientific pipelines in distributed environments [PDF]
, 2018 Real-world scientific applications often encompass end-to-end data processing pipelines composed of a large number of interconnected computational tasks of various granularity.
Ashby, Thomas J. +7 more
core +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Utilizing Molecular Descriptor Importance to Enhance Endpoint Predictions
ToxicsQuantitative structure–activity relationship (QSAR) models are essential for predicting endpoints that are otherwise challenging to estimate using other in silico approaches.
Benjamin Bajželj +2 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
CDK-Taverna: an open workflow environment for cheminformatics
BMC Bioinformatics, 2010 Background Small molecules are of increasing interest for bioinformatics in areas such as metabolomics and drug discovery. The recent release of large open access chemistry databases generates a demand for flexible tools to process them and discover new ...
Zielesny Achim +3 more
doaj +1 more source
Gaussian Processes for Predictive QSAR Modeling of Chromatographic Processes
Biotechnology and Bioengineering, EarlyView.ABSTRACT Chromatography is a key unit operation in the biopharmaceutical manufacturing process used for protein purification and polishing. Design and optimization of these processes are resource‐intensive resulting from the complex combinatorial design space.
Harini Narayanan +7 more
wiley +1 more source