AI Medical Compendium Journal:
Computational biology and chemistry

Showing 151 to 160 of 191 articles

Physicochemical property based computational scheme for classifying DNA sequence elements of Saccharomyces cerevisiae.

Computational biology and chemistry
GenerationE of huge "omics" data necessitates the development and application of computational methods to annotate the data in terms of biological features. In the context of DNA sequence, it is important to unravel the hidden physicochemical signatu...

Prediction of drug-target interaction by integrating diverse heterogeneous information source with multiple kernel learning and clustering methods.

Computational biology and chemistry
BACKGROUND: Identification of potential drug-target interaction pairs is very important for pharmaceutical innovation and drug discovery. Numerous machine learning-based and network-based algorithms have been developed for predicting drug-target inte...

Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients.

Computational biology and chemistry
Paraquat (PQ) poisoning seriously harms the health of humanity. An effective diagnostic method for paraquat poisoned patients is a crucial concern. Nevertheless, it's difficult to identify the patients with low intake of PQ or delayed treatment. Here...

Laplacian regularized low-rank representation for cancer samples clustering.

Computational biology and chemistry
Cancer samples clustering based on biomolecular data has been becoming an important tool for cancer classification. The recognition of cancer types is of great importance for cancer treatment. In this paper, in order to improve the accuracy of cancer...

Sequence-based analysis and prediction of lantibiotics: A machine learning approach.

Computational biology and chemistry
Lantibiotics, an important group of ribosomally synthesized peptides, represent an important arsenal of novel promising antimicrobials showing high potency in fighting against the prevalence of antibiotic resistance among microbial pathogens. However...

C-PUGP: A cluster-based positive unlabeled learning method for disease gene prediction and prioritization.

Computational biology and chemistry
Disease gene detection is an important stage in the understanding disease processes and treatment. Some candidate disease genes are identified using many machine learning methods Although there are some differences in these methods including feature ...

Statistical and artificial neural network-based analysis to understand complexity and heterogeneity in preeclampsia.

Computational biology and chemistry
Preeclampsia is a pregnancy associated disease. It is characterized by high blood pressure and symptoms that are indicative of damage to other organ systems, most often involving the liver and kidneys. If left untreated, the condition could be fatal ...

Sequentially distant but structurally similar proteins exhibit fold specific patterns based on their biophysical properties.

Computational biology and chemistry
The Three-dimensional structure of a protein depends on the interaction between their amino acid residues. These interactions are in turn influenced by various biophysical properties of the amino acids. There are several examples of proteins that sha...

A survey of recently emerged genome-wide computational enhancer predictor tools.

Computational biology and chemistry
The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, his...

Markovian encoding models in human splice site recognition using SVM.

Computational biology and chemistry
Splice site recognition is among the most significant and challenging tasks in bioinformatics due to its key role in gene annotation. Effective prediction of splice site requires nucleotide encoding methods that reveal the characteristics of DNA sequ...