AI Medical Compendium Journal:
Computational biology and chemistry

Showing 161 to 170 of 191 articles

Imidazolium ionic liquids as effective antiseptics and disinfectants against drug resistant S. aureus: In silico and in vitro studies.

Computational biology and chemistry
This paper describes Quantitative Structure-Activity Relationships (QSAR) studies, molecular docking and in vitro antibacterial activity of several potent imidazolium-based ionic liquids (ILs) against S. aureus ATCC 25923 and its clinical isolate. Sm...

In silico toxicity profiling of natural product compound libraries from African flora with anti-malarial and anti-HIV properties.

Computational biology and chemistry
This paper describes an analysis of the diversity and chemical toxicity assessment of three chemical libraries of compounds from African flora (the p-ANAPL, AfroMalariaDb, and Afro-HIV), respectively containing compounds exhibiting activities against...

Predicting lysine glycation sites using bi-profile bayes feature extraction.

Computational biology and chemistry
Glycation is a nonenzymatic post-translational modification which has been found to be involved in various biological processes and closely associated with many metabolic diseases. The accurate identification of glycation sites is important to unders...

HashGO: hashing gene ontology for protein function prediction.

Computational biology and chemistry
Gene ontology (GO) is a standardized and controlled vocabulary of terms that describe the molecular functions, biological roles and cellular locations of proteins. GO terms and GO hierarchy are regularly updated as the accumulated biological knowledg...

Factors analysis of protein O-glycosylation site prediction.

Computational biology and chemistry
To improve the prediction accuracy of O-glycosylation sites, and analyze the structure of the O-glycosylation sites, factor analysis based prediction is proposed in this study. Our studies show that factor analysis strongly boosts machine learning al...

Enzyme classification using multiclass support vector machine and feature subset selection.

Computational biology and chemistry
Proteins are the macromolecules responsible for almost all biological processes in a cell. With the availability of large number of protein sequences from different sequencing projects, the challenge with the scientist is to characterize their functi...

Computational model for vitamin D deficiency using hair mineral analysis.

Computational biology and chemistry
Vitamin D deficiency is prevalent in the Arabian Gulf region, especially among women. Recent studies show that the vitamin D deficiency is associated with a mineral status of a patient. Therefore, it is important to assess the mineral status of the p...

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

Computational biology and chemistry
The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular...

Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images.

Computational biology and chemistry
Protein structure prediction and analysis are more significant for living organs to perfect asses the living organ functionalities. Several protein structure prediction methods use neural network (NN). However, the Hidden Markov model is more interpr...

Node-based differential network analysis in genomics.

Computational biology and chemistry
Gene dependency networks often undergo changes in response to different conditions. Understanding how these networks change across two conditions is an important task in genomics research. Most previous differential network analysis approaches assume...