AI Medical Compendium Journal:
Computational biology and chemistry

Showing 131 to 140 of 191 articles

ICTC-RAAC: An improved web predictor for identifying the types of ion channel-targeted conotoxins by using reduced amino acid cluster descriptors.

Computational biology and chemistry
Conotoxins are small peptide toxins which are rich in disulfide and have the unique diversity of sequences. It is significant to correctly identify the types of ion channel-targeted conotoxins because that they are considered as the optimal pharmacol...

L-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification.

Computational biology and chemistry
With the development of cancer research, various gene expression datasets containing cancer information show an explosive growth trend. In addition, due to the continuous maturity of single-cell RNA sequencing (scRNA-seq) technology, the protein info...

iPiDA-sHN: Identification of Piwi-interacting RNA-disease associations by selecting high quality negative samples.

Computational biology and chemistry
As a large group of small non-coding RNAs (ncRNAs), Piwi-interacting RNAs (piRNAs) have been detected to be associated with various diseases. Identifying disease associated piRNAs can provide promising candidate molecular targets to promote the drug ...

A review of Cloud computing technologies for comprehensive microRNA analyses.

Computational biology and chemistry
Cloud computing revolutionized many fields that require ample computational power. Cloud platforms may also provide huge support for microRNA analysis mainly through disclosing scalable resources of different types. In Clouds, these resources are ava...

ncRDeep: Non-coding RNA classification with convolutional neural network.

Computational biology and chemistry
A non-coding RNA (ncRNA) is a kind of RNA that is not converted into protein, however, it is involved in many biological processes, diseases, and cancers. Numerous ncRNAs have been identified and classified with high throughput sequencing technology....

A deep learning approach based on convolutional LSTM for detecting diabetes.

Computational biology and chemistry
Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or the body cannot effectively utilize the produced insulin. If it remains unidentified and untreated, then it could be very deadliest. One can lead a he...

Prognostic prediction of carcinoma by a differential-regulatory-network-embedded deep neural network.

Computational biology and chemistry
The accurate prognostic prediction is essential for precise diagnosis and treatment of carcinoma. In addition to clinical survival prediction method, many computational methods based on transcriptomic data have been proposed to build the prediction m...

A machine learning approach to select features important to stroke prognosis.

Computational biology and chemistry
Ischemic stroke is a common neurological disorder, and is still the principal cause of serious long-term disability in the world. Selection of features related to stroke prognosis is highly valuable for effective intervention and treatment. In this s...

Intelligent system based on data mining techniques for prediction of preterm birth for women with cervical cerclage.

Computational biology and chemistry
Preterm birth, defined as a delivery before 37 weeks' gestation, continues to affect 8-15% of all pregnancies and is associated with significant neonatal morbidity and mortality. Effective prediction of timing of delivery among women identified to be...

Design of (quinolin-4-ylthio)carboxylic acids as new Escherichia coli DNA gyrase B inhibitors: machine learning studies, molecular docking, synthesis and biological testing.

Computational biology and chemistry
Spread of multidrug-resistant Escherichia coli clinical isolates is a main problem in the treatment of infectious diseases. Therefore, the modern scientific approaches in decision this problem require not only a prevention strategy, but also the deve...