Molecular similarity in chemical informatics and predictive toxicity modeling: From quantitative read-across (q-RA) to quantitative read-across structure–activity …
This article aims to provide a comprehensive critical, yet readable, review of general interest
to the chemistry community on molecular similarity as applied to chemical informatics and …
to the chemistry community on molecular similarity as applied to chemical informatics and …
How to correctly develop q-RASAR models for predictive cheminformatics
One of the earliest and simplest forms of in silico predictive cheminformatics is the
Quantitative Structure-Activity Relationship (QSAR). This algorithm aims to develop a …
Quantitative Structure-Activity Relationship (QSAR). This algorithm aims to develop a …
The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a …
With the exponential progress in the field of cheminformatics, the conventional modeling
approaches have so far been to employ supervised and unsupervised machine learning …
approaches have so far been to employ supervised and unsupervised machine learning …
[HTML][HTML] Organic Sunscreens and Their Products of Degradation in Biotic and Abiotic Conditions—In Silico Studies of Drug-Likeness and Human Placental Transport
A total of 16 organic sunscreens and over 160 products of their degradation in biotic and
abiotic conditions were investigated in the context of their safety during pregnancy. Drug …
abiotic conditions were investigated in the context of their safety during pregnancy. Drug …
ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity …
Due to the lack of experimental toxicity data for environmental chemicals, there arises a
need to fill data gaps by in silico approaches. One of the most commonly used in silico …
need to fill data gaps by in silico approaches. One of the most commonly used in silico …
Cheminformatic Read-Across Approach Revealed Ultraviolet Filter Cinoxate as an Obesogenic Peroxisome Proliferator-Activated Receptor γ Agonist
S An, IG Park, SY Hwang, J Gong, Y Lee… - Chemical Research …, 2024 - ACS Publications
This study introduces a novel cheminformatic read-across approach designed to identify
potential environmental obesogens, substances capable of disrupting metabolism and …
potential environmental obesogens, substances capable of disrupting metabolism and …
Transparent Machine Learning Model to Understand Drug Permeability through the Blood–Brain Barrier
The blood–brain barrier (BBB) selectively regulates the passage of chemical compounds
into and out of the central nervous system (CNS). As such, understanding the permeability of …
into and out of the central nervous system (CNS). As such, understanding the permeability of …
Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs
We have adopted the classification Read-Across Structure–Activity Relationship (c-RASAR)
approach in the present study for machine-learning (ML)-based model development from a …
approach in the present study for machine-learning (ML)-based model development from a …
BBBper: A Machine Learning-based Online Tool for Blood-Brain Barrier (BBB) Permeability Prediction
Aims Neuronal disorders have affected more than 15% of the world's population, signifying
the importance of continued design and development of drugs that can cross the Blood …
the importance of continued design and development of drugs that can cross the Blood …
Innovative strategies for the quantitative modeling of blood–brain barrier (BBB) permeability: harnessing the power of machine learning-based q-RASAR approach
In the current research, we have unveiled an advanced technique termed the quantitative
read-across structure–activity relationship (q-RASAR) framework to harness the power of …
read-across structure–activity relationship (q-RASAR) framework to harness the power of …