Data driven toxicity assessment of organic chemicals against Gammarus species using QSAR approach

L Yang, R Tian, Z Li, X Ma, H Wang, W Sun - Chemosphere, 2023 - Elsevier
Nowadays, organic chemicals play an essential role in almost all walks of life and have
become indispensable to modern society. However, the continually synthesized chemicals …

ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity …

A Banerjee, K Roy - Environmental Science: Processes & Impacts, 2024 - pubs.rsc.org
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 …

[HTML][HTML] In Silico Modeling and Structural Analysis of Soluble Epoxide Hydrolase Inhibitors for Enhanced Therapeutic Design

S Sar, S Mitra, P Panda, SC Mandal, N Ghosh… - Molecules, 2023 - mdpi.com
Human soluble epoxide hydrolase (sEH), a dual-functioning homodimeric enzyme with
hydrolase and phosphatase activities, is known for its pivotal role in the hydrolysis of …

Integrated Transfer Learning and Multitask Learning Strategies to Construct Graph Neural Network Models for Predicting Bioaccumulation Parameters of Chemicals

Z Xiao, M Zhu, J Chen, Z You - Environmental Science & …, 2024 - ACS Publications
Accurate prediction of parameters related to the environmental exposure of chemicals is
crucial for the sound management of chemicals. However, the lack of large data sets for …

[HTML][HTML] Modelling of novel bornoel analogs as Influenza A Virus inhibitors through genetic function approximation, comparative molecular fields, molecular docking …

M Abdullahi, A Uzairu, GA Shallangwa, PA Mamza… - Intelligent …, 2024 - Elsevier
Abstract Influenza A Virus (IAV) is a human respiratory pathogen prone to mutations and
genome re-assortment leading to global pandemics. In this study, we applied the molecular …

[HTML][HTML] Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model

J Liu, Y Zhang, C Yi, R Zhang, S Yang, T Liu, D Jia… - Lubricants, 2023 - mdpi.com
Two quantitative structure–property relationship (QSPR) models of hindered phenolic
antioxidants in lubricating oils were established to help guide the molecular structure design …

Exploratory Study of Differentially Expressed Genes of Peripheral Blood Monocytes in Patients with Carotid Atherosclerosis

J Chen, F Xu, X Mo, Y Cheng, L Wang… - … Chemistry & High …, 2024 - ingentaconnect.com
Background: The abundance of circulating monocytes is closely associated with the
development of atherosclerosis in humans. Objective: This study aimed to further research …

Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)

EA Medina, S He, A Daghighi, K Iduoku… - 2024 - preprints.org
The dielectric constant (ε) reflects the ability of a material to align and orient electrical
dipoles within its structure in response to an externally applied electric field; the greater the …

Standalone methodology for building QSAR models: an antioxidant QSAR model of di (hetero) aryl amines and amides as a case study

C Mateus, RMV Abreu - 2024 - researchsquare.com
QSAR modeling is a methodology used in various scientific fields to correlate molecular
descriptors to the properties or biological activities of compounds of interest. Several steps …