Results 41 to 50 of about 36,144 (247)

QSAR Model for Predicting Antioxidan Capacity of Some Polyphenolic Antioxidants [PDF]

, 2016
Quantitative structure–activity relationship model (QSAR models) is useful method for predicting antioxidant capacity of a molecule based on some chemical-physics properties.
Milenkovic, Dejan, Filipovic, Milos, Djorovic, Jelena, Jeremic, Svetlana, Markovic, Zoran   +4 more
core  

Nonequivalent Effects of Diverse LogP Algorithms in Three QSAR Studies

, 2015
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Despite of the availability and facility of accessing several algorithms for calculation of LogP in QSA(P)R studies, articles typically do not describe the selection procedure for the method ...
de Melo, EB, Ferreira, MMC
core   +1 more source

Environmental impact of PFAS: Filling data gaps using theoretical quantum chemistry and QSPR modeling

Environment International
Per- and polyfluorinated alkyl substances (PFAS), known for their widespread environmental presence and slow degradation, pose significant concerns. Of the approximately 10,000 known PFAS, only a few have undergone comprehensive testing, resulting in ...
Michalina Mudlaff, Anita Sosnowska, Leonid Gorb, Natalia Bulawska, Karolina Jagiello, Tomasz Puzyn   +5 more
doaj   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for acute oral toxicity of benzene derivatives - Acute Toxic Class Method. Q13-42-0029. Molcode Ltd., 2009.

, 2020
This QSAR model corresponds to the QMRF Q13-42-0029 "QSAR for acute oral toxicity of benzene derivatives - Acute Toxic Class Method" from the JRC QSAR Model ...

core   +1 more source

Antioxidant activity of some natural essential oils in Vietnam: Comparison between QSAR simulation and experimental study

Tạp chí Khoa học Đại học Huế: Khoa học Tự nhiên, 2020
The antioxidant activity of essential oils from leaves of Piper betle L. (T) and Cleistocalyx operculatus L. (V) and aerial parts of Ageratum conyzoides L. (H), indigenously grown in Thua Thien Hue province, Vietnam, is investigated.
Tran Thi Ai My, Le Trung Hieu, Nguyen Thi Thanh Hai, Ton Nu My Phuong, Huynh Thi Phuong Loan, Bui Thi Phuong Thuy, Nguyen Thi Ai Nhung   +6 more
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

QSAR of Clerodane Diterpenoids with Cytotoxic and Antitumoral Activity Against V-79 Cells

, 2015
This work deals with diterpenoids of the clerodane type, compounds isolated from the extracts of different plant organs from trees mainly of the Flacourtiaceae family.
Takahata, Y, Cramer, B
core   +1 more source

Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for algae toxicity of benzene derivatives. Q13-32-0028. Molcode Ltd., 2009.

, 2020
This QSAR model corresponds to the QMRF Q13-32-0028 "QSAR for algae toxicity of benzene derivatives" from the JRC QSAR Model ...

core   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source