AI Medical Compendium Journal:
Combinatorial chemistry & high throughput screening

Showing 31 to 40 of 68 articles

Antioxidant Proteins' Identification Based on Support Vector Machine.

Combinatorial chemistry & high throughput screening
BACKGROUND: Evidence have increasingly indicated that for human disease, cell metabolism are deeply associated with proteins. Structural mutations and dysregulations of these proteins contribute to the development of the complex disease. Free radical...

Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia can be classified into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML)...

Identification of Anti-cancer Peptides Based on Multi-classifier System.

Combinatorial chemistry & high throughput screening
AIMS AND OBJECTIVE: Cancer is one of the deadliest diseases, taking the lives of millions every year. Traditional methods of treating cancer are expensive and toxic to normal cells. Fortunately, anti-cancer peptides (ACPs) can eliminate this side eff...

New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes.

Combinatorial chemistry & high throughput screening
BACKGROUND: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To date, many genes have been discovered to be related to rhinovirus infection. However, the pathogenic mechanism of rhinovirus is difficu...

Prediction of Citrullination Sites on the Basis of mRMR Method and SNN.

Combinatorial chemistry & high throughput screening
BACKGROUND: Citrullination, an important post-translational modification of proteins, alters the molecular weight and electrostatic charge of the protein side chains. Citrulline, in protein sequences, is catalyzed by a class of Peptidyl Arginine Deim...

Enrichment of Up-regulated and Down-regulated Gene Clusters Using Gene Ontology, miRNAs and lncRNAs in Colorectal Cancer.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: It is interesting to find the gene signatures of cancer stages based on the omics data. The aim of study was to evaluate and to enrich the array data using gene ontology and ncRNA databases in colorectal cancer.

Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: The accurate identification of protein-ligand binding sites helps elucidate protein function and facilitate the design of new drugs. Machine-learning-based methods have been widely used for the prediction of protein-ligand binding ...

Recognition of Lung Adenocarcinoma-specific Gene Pairs Based on Genetic Algorithm and Establishment of a Deep Learning Prediction Model.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Lung cancer is a disease with a dismal prognosis and is the major cause of cancer deaths in many countries. Nonetheless, rapid technological developments in genome science guarantees more effective prevention and treatment strategi...

Constructing a Risk Prediction Model for Lung Cancer Recurrence by Using Gene Function Clustering and Machine Learning.

Combinatorial chemistry & high throughput screening
OBJECTIVE: A significant proportion of patients with early non-small cell lung cancer (NSCLC) can be cured by surgery. The distant metastasis of tumors is the most common cause of treatment failure. Precisely predicting the likelihood that a patient ...