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Crystallization

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Formulation and solid state characterization of carboxylic acid-based co-crystals of tinidazole: An approach to enhance solubility.

Polimery w medycynie
BACKGROUND: Tinidazole (TNZ) is an anti-parasite drug used in the treatment of a variety of amebic and parasitic infections. It has low solubility in aqueous media and is categorized under Class II of the Biopharmaceutical Classification System.

3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods.

PloS one
Boosting is a family of supervised learning algorithm that convert a set of weak learners into a single strong one. It is popular in the field of object tracking, where its main purpose is to extract the position, motion, and trajectory from various ...

Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments.

Journal of chemical information and modeling
Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules is so vast that only a limited exploration with the traditional methods can be ever possible. ...

Analysis of crystallization phenomenon in Indian honey using molecular dynamics simulations and artificial neural network.

Food chemistry
Molecular dynamics simulation was performed on sugar profile and moisture content-based mixture systems of six Indian honey samples. Comparative studies were performed to understand the interactive effects of fructose, glucose, sucrose, maltose and w...

Inexpensive robotic system for standard and fluorescent imaging of protein crystals.

Acta crystallographica. Section F, Structural biology communications
Protein-crystallization imaging and classification is a labor-intensive process typically performed either by humans or by instruments that currently cost well over $100 000. This cost puts the use of crystallization-trial imaging outside the reach o...

Toward Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks.

Journal of chemical information and modeling
The surface energy of inorganic crystals is important in understanding experimentally relevant surface properties and designing materials for many applications. Predictive methods and data sets exist for surface energies of monometallic crystals. How...

Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability.

Journal of chemical information and modeling
Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chemical structure representation. The classical approach ...

Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II.

Journal of drug targeting
Bone morphogenetic protein-2 (BMP-2) is a key regulator of bone formation, growth and regeneration, which contains a conformational wrist epitope and a linear knuckle epitope that are functionally responsible for the protein by mediating its interact...

CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Improving the accuracy of predicting protein crystallization is very important for protein crystallization projects, which is a critical step for the determination of protein structure by X-ray crystallography. At present, many machine learning metho...

Protein Crystallization Identification via Fuzzy Model on Linear Neighborhood Representation.

IEEE/ACM transactions on computational biology and bioinformatics
X-ray crystallography is the most popular approach for analyzing protein 3D structure. However, the success rate of protein crystallization is very low (2-10 percent). To reduce the cost of time and resources, lots of computation-based methods are de...