AI Medical Compendium Journal:
Molecular informatics

Showing 91 to 100 of 113 articles

Machine Learning Estimation of Atom Condensed Fukui Functions.

Molecular informatics
To enable the fast estimation of atom condensed Fukui functions, machine learning algorithms were trained with databases of DFT pre-calculated values for ca. 23,000 atoms in organic molecules. The problem was approached as the ranking of atom types w...

Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.

Molecular informatics
tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A...

Inferring Association between Compound and Pathway with an Improved Ensemble Learning Method.

Molecular informatics
Emergence of compound molecular data coupled to pathway information offers the possibility of using machine learning methods for compound-pathway associations' inference. To provide insights into the global relationship between compounds and their af...

Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

Molecular informatics
The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important resea...

Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation.

Molecular informatics
In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict meltin...

Cheminformatics Based Machine Learning Models for AMA1-RON2 Abrogators for Inhibiting Plasmodium falciparum Erythrocyte Invasion.

Molecular informatics
Malaria remains a dreadful disease by putting every year about 3.4 billion people at risk and resulting into mortality of 627 thousand people worldwide. Existing therapies based upon Quinines and Artemisinin-based combination therapies have started s...

Quantitative Regression Models for the Prediction of Chemical Properties by an Efficient Workflow.

Molecular informatics
Rapid safety assessment is more and more needed for the increasing chemicals both in chemical industries and regulators around the world. The traditional experimental methods couldn't meet the current demand any more. With the development of the info...

Greedy and Linear Ensembles of Machine Learning Methods Outperform Single Approaches for QSPR Regression Problems.

Molecular informatics
The application of Machine Learning to cheminformatics is a large and active field of research, but there exist few papers which discuss whether ensembles of different Machine Learning methods can improve upon the performance of their component metho...

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

Molecular informatics
The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal p...

Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells.

Molecular informatics
Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable...