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Combined molecular dynamics and neural network method for predicting protein antifreeze activity.

Proceedings of the National Academy of Sciences of the United States of America
Antifreeze proteins (AFPs) are a diverse class of proteins that depress the kinetically observable freezing point of water. AFPs have been of scientific interest for decades, but the lack of an accurate model for predicting AFP activity has hindered ...

Optimization and modelling of enzymatic polymerization of ε-caprolactone to polycaprolactone using Candida Antartica Lipase B with response surface methodology and artificial neural network.

Enzyme and microbial technology
Recently enzymatic catalysts have replaced organic and organometallic catalysts in the synthesis of bio-resorbable polymers. Enzymatic polymerization is considered as an alternative to conventional polymerization as they are less toxic, environmental...

Investigation of magnetic silica with thermoresponsive chitosan coating for drug controlled release and magnetic hyperthermia application.

Materials science & engineering. C, Materials for biological applications
In this study, a drug delivery system for chemo-hyperthermia applications is proposed and fabricated. The delivery system consists of magnetic-silica (MagSi) particles being encapsulated within a pH/thermo-responsive chitosan‑g‑N‑isopropylacrylamide ...

Specific and sensitive ELISA for measurement of IgE-binding variations of milk allergen β-lactoglobulin in processed foods.

Analytica chimica acta
Immunochemical detection of food allergens is usually based on the use of polyclonal or monoclonal immunoglobulins G (IgG) antibodies. However, due to differences in epitopes recognition between IgG and IgE, an epitope modification during food proces...

The pharmacokinetics and pharmacodynamics of intravenous hydromorphone in horses.

Veterinary anaesthesia and analgesia
OBJECTIVE: Describe the pharmacokinetics and pharmacodynamics of intravenous hydromorphone in healthy horses.

Pectin extraction from Helianthus annuus (sunflower) heads using RSM and ANN modelling by a genetic algorithm approach.

International journal of biological macromolecules
In this work, Response Surface Methodology (RSM) and Artificial Neural Network coupled with genetic algorithm (ANN-GA) have been used to develop a model and optimise the conditions for the extraction of pectin from sunflower heads. Input parameters w...

Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

Environmental science and pollution research international
River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network model...

A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features.

PloS one
Xylanases are hydrolytic enzymes which based on physicochemical properties, structure, mode of action and substrate specificities are classified into various glycoside hydrolase (GH) families. The purpose of this study is to show that the activity of...

Variable importance for sustaining macrophyte presence via random forests: data imputation and model settings.

Scientific reports
Data sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data i...

Predicting Thermodynamic Properties of Alkanes by High-Throughput Force Field Simulation and Machine Learning.

Journal of chemical information and modeling
Knowledge of the thermodynamic properties of molecules is essential for chemical process design and the development of new materials. Experimental measurements are often expensive and not environmentally friendly. In the past, studies using molecular...