Results 11 to 20 of about 6,707 (205)

An Atom Counting QSPR Protocol [PDF]

QSAR & Combinatorial Science, 2008
AbstractA simple descriptor, viz the number of carbon (NC)/non‐hydrogenic (NNH) atoms present in a molecule, is proposed for the development of useful Quantitative Structure–Property–Relationship (QSPR) models. This work is prompted by that of Randic and Basak (J. Chem. Inf. Comput. Sci.
Santanab Giri, Dehesh R. Roy, Sofie Van Damme, Patrick Bultinck, Venkatesan Subramanian, Pratim K. Chattaraj   +5 more
openaire   +2 more sources

The QSPR-THESAURUS: The Online Platform of the CADASTER Project [PDF]

Alternatives to Laboratory Animals, 2014
The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and ...
Brandmaier, S., Peijnenburg, W., Durjava, M. K., Kolar, B., GRAMATICA, PAOLA, PAPA, ESTER, Bhhatarai, B., Kovarich, S., Cassani, S., Roy, P. P., Rahmberg, M., Öberg, T., Jeliazkova, N., Golsteijn, L., Comber, M., Charochkina, L., Novotarskyi, S., Sushko, I., Abdelaziz, A., D'Onofrio, E., Kunwar, P., Ruggiu, F., Tetko, I. V.   +22 more
core   +5 more sources

Modelling Flavour Release through Quantitative Structure Property Relationships (QSPR) [PDF]

CHIMIA, 2001
The use of QSPR to explain the partition behaviour of flavour compounds in different matrices and to predict dynamic flavour release from certain food systems is described.
Andrew J. Taylor, Robert S.T. Linforth
doaj   +4 more sources

Mixture-Quantitative Structure-Property Relationship Approaches for Jet Fuel-Component Blends: A Review. [PDF]

Mol Inform
A literature review of QSPR approaches to predict jet fuel properties. It exposes the fundamental principles of QSPR and illustrates pure‐compound QSPR through examples of applications for jet fuel components. Mixture‐QSPR (M‐QSPR) modeling specificities are addressed: mixtures representation, design of descriptors for mixtures, and impact on internal ...
Yeghyan E, Creton B, Matrat M, Marcou G.
europepmc   +2 more sources

Eccentric indices based QSPR evaluation of drugs for schizophrenia treatment

Heliyon
Schizophrenia is a long-term, serious mental health condition that affects how a person thinks, perceives, and behaves. This disorder often results in substantial difficulties in social interactions and work performance.
Muneeba Mansha, Sarfraz Ahmad, Zahid Raza   +2 more
doaj   +2 more sources

GTI-space : the space of generalized topological indices [PDF]

, 2008
A new extension of the generalized topological indices (GTI) approach is carried out torepresent 'simple' and 'composite' topological indices (TIs) in an unified way.
Matamala, A.R., Matamala, Adelio R., Estrada, Ernesto, Ramon y Cajal program Spain (Funder), , Ramon y Cajal program Spain (Funder), Estrada, E.   +5 more
core   +4 more sources

Quantitative Structure-Property Relationships (QSPR) to Predict Surface Tension and Electrical Conductivity of Ionic Liquid Propellants [PDF]

, 2023
Quantitative structure property relationships (QSPR) mine data sets of experimentally measured properties to predict different material properties through mathematical regression and machine learning.
Steven D., Chambreau, Debasis, Sengupta, David A., Newsome, Ghanshyam L., Vaghjiani, Daniel , Yos   +4 more
core   +1 more source

Molecular descriptor driven QSPR modeling of Papp, TEER and Efflux Ratio from Caco-2 cells using machine learning for various phytochemicals. [PDF]

J Sci Food Agric
Abstract BACKGROUND The present study aimed to develop and validate quantitative structure–property relationship (QSPR) models for predicting permeability related bioavailability indicators including apparent permeability (Papp), trans‐epithelial electrical resistance (TEER) and efflux ratio (ER) based on molecular descriptors (n = 5003) of 83 ...
Kim JW, Cong R, Park JS, Park K, Kang K, Shim SM.   +5 more
europepmc   +2 more sources

QSPR AND ARTIFICIAL NEURAL NETWORK PREDICTIONS OF HYPERGOLIC IGNITION DELAYS FOR ENERGETIC IONIC LIQUIDS [PDF]

, 2023
Due to their negligible volatility, energetic ionic liquids are being considered as next generation hypergolic fuels for replacing toxic monomethylhydrazine.
Debasis, Sengupta, Maciej Z., Pindera, Ghanshyam L., Vaghjiani, J. Vernon , Cole   +3 more
core   +1 more source

QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility

Inorganics, 2023
Background: The system of self-consistent models is an attempt to develop a tool to assess the predictive potential of various approaches by considering a group of random distributions of available data into training and validation sets. Considering many different splits is more informative than considering a single model.
Alla P. Toropova, Andrey A. Toropov, Natalja Fjodorova   +2 more
openaire   +2 more sources