Results 51 to 60 of about 2,775 (180)

Harary-Albertson index of graphs [PDF]

Contributions to Mathematics, 2021
Zhen Lin
doaj   +1 more source

Feature Learning applied to the Estimation of Tensile Strength at Break in Polymeric Material Design

Journal of Integrative Bioinformatics, 2016
Several feature extraction approaches for QSPR modelling in Cheminformatics are discussed in this paper. In particular, this work is focused on the use of these strategies for predicting mechanical properties, which are relevant for the design of ...
Fiorella Cravero, Jimena Martínez M., Gustavo Vazquez, Díaz Mónica F., Ignacio Ponzoni   +4 more
doaj   +1 more source

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   +1 more source

Reliable Apparent Permeability Prediction Through Benchmarking, Stability, Uncertainty Quantification, and Explainable Machine Learning

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Apparent permeability (Papp$$ {P}_{app} $$) of a drug molecule serves as a principal indicator of drug absorption for pharmacokinetic modeling, and accurate prediction of Papp$$ {P}_{app} $$ values using machine learning would avoid time‐consuming and expensive In Vitro experiments.
Rajdeep Mondal, Rajith K. R. Rajoli, Andrew Owen, Soumitra Samanta   +3 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, Volume 72, Issue 7, July 2026.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

QSPR modeling of flash points: An update

Journal of Molecular Graphics and Modelling, 2007
Quantitative structure-property relationship (QSPR) models for the flash points of 758 organic compounds are developed using geometrical, topological, quantum mechanical and electronic descriptors calculated by CODESSA PRO software. Multilinear regression models link the structures to their reported flash point values.
Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, FL 32611, USA ( host institution ), Katritzky, Alan R., Stoyanova-Slavova, Iva B., Dobchev, Dimitar A., Karelson, Mati   +4 more
openaire   +3 more sources

Metronomic Chemotherapy in Ovarian Cancer: Current Scenario and AI‐Integrated Future Strategies

Cancer Reports, Volume 9, Issue 7, July 2026.
ABSTRACT Background Ovarian cancer (OC) is a globally prevalent malignancy associated with a high mortality rate and marked biological heterogeneity, with most cases arising from epithelial cells and presenting as serous, endometrioid, or clear cell subtypes.
Ravi Chauhan, Suraja Kumar Das, Lakshay Malhotra, Rajeev Goyal, Sameer Mirza, Khushi Nehra, Maysaloun Merhi, Ammira S. Al‐Shabeeb Akil, Shahab Uddin, Shweta Tripathi, Ajaz A. Bhat, Mayank Singh   +11 more
wiley   +1 more source

Topological Descriptors of Colorectal Cancer Drugs and Characterizing Physical Properties Via QSPR Analysis

International Journal of Analytical Chemistry
Topological descriptors and QSPR analysis are statistical techniques that are highly beneficial for analyzing various physical and chemical characteristics of molecular graphs without necessitating expensive and time-consuming laboratory experiments. The
Sumiya Nasir
doaj   +1 more source

Using generalized quantitative structure–property relationship (QSPR) models to predict host cell protein retention in ion‐exchange chromatography

Journal of Chemical Technology &Biotechnology, Volume 101, Issue 7, Page 1420-1428, July 2026.
Abstract BACKGROUND Selecting an optimal chromatography resin during biopharmaceutical downstream process development is a great challenge. This is especially the case for recombinant subunit vaccines, where product properties vary greatly and recovery often involves cell lysis, which yields a complex mixture of different host cell materials. Host cell
Tim Neijenhuis, Olivier Le Bussy, Geoffroy Geldhof, Marieke E Klijn, Marcel Ottens   +4 more
wiley   +1 more source

QSPR Model for Regulatory Purpose: from Development to Integration into the QSAR Toolbox

Chemical Engineering Transactions, 2016
Quantitative Structure-Property Relationships (QSPR) are predictive methods of macroscopic properties of substances based on their only molecular structures.
Guillaume Fayet, Patricia Rotureau
doaj   +1 more source