AIMC Topic: Machine Learning

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Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma.

Briefings in bioinformatics
Uveal melanoma (UVM) is the most common primary intraocular human malignancy with a high mortality rate. Aberrant DNA methylation has rapidly emerged as a diagnostic and prognostic signature in many cancers. However, such DNA methylation signature av...

Topological network measures for drug repositioning.

Briefings in bioinformatics
Drug repositioning has received increased attention since the past decade as several blockbuster drugs have come out of repositioning. Computational approaches are significantly contributing to these efforts, of which, network-based methods play a ke...

A comprehensive survey on computational methods of non-coding RNA and disease association prediction.

Briefings in bioinformatics
The studies on relationships between non-coding RNAs and diseases are widely carried out in recent years. A large number of experimental methods and technologies of producing biological data have also been developed. However, due to their high labor ...

Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning.

Briefings in bioinformatics
Thyroid nodules are neoplasms commonly found among adults, with papillary thyroid carcinoma (PTC) being the most prevalent malignancy. However, current diagnostic methods often subject patients to unnecessary surgical burden. In this study, we develo...

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Briefings in bioinformatics
Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healthy cells directly, they have been extensively studied. Many peptide-based drugs are currently evalua...

ITP-Pred: an interpretable method for predicting, therapeutic peptides with fused features low-dimension representation.

Briefings in bioinformatics
The peptide therapeutics market is providing new opportunities for the biotechnology and pharmaceutical industries. Therefore, identifying therapeutic peptides and exploring their properties are important. Although several studies have proposed diffe...

Recent advances in network-based methods for disease gene prediction.

Briefings in bioinformatics
Disease-gene association through genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms that correlate with specific diseases needs statistical analysis of associations. Considering the ...

ChemFLuo: a web-server for structure analysis and identification of fluorescent compounds.

Briefings in bioinformatics
BACKGROUND: Fluorescent detection methods are indispensable tools for chemical biology. However, the frequent appearance of potential fluorescent compound has greatly interfered with the recognition of compounds with genuine activity. Such fluorescen...

Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus.

Briefings in bioinformatics
BACKGROUND: A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and effective prediction of antibiotic resistance. Since delays in the traditional antibiotic susceptibil...

TrimNet: learning molecular representation from triplet messages for biomedicine.

Briefings in bioinformatics
MOTIVATION: Computational methods accelerate drug discovery and play an important role in biomedicine, such as molecular property prediction and compound-protein interaction (CPI) identification. A key challenge is to learn useful molecular represent...