AIMC Topic: Neural Networks, Computer

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Inference of gene regulatory networks based on directed graph convolutional networks.

Briefings in bioinformatics
Inferring gene regulatory network (GRN) is one of the important challenges in systems biology, and many outstanding computational methods have been proposed; however there remains some challenges especially in real datasets. In this study, we propose...

TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Briefings in bioinformatics
Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as a...

MvMRL: a multi-view molecular representation learning method for molecular property prediction.

Briefings in bioinformatics
Effective molecular representation learning is very important for Artificial Intelligence-driven Drug Design because it affects the accuracy and efficiency of molecular property prediction and other molecular modeling relevant tasks. However, previou...

Hierarchical multimodal self-attention-based graph neural network for DTI prediction.

Briefings in bioinformatics
Drug-target interactions (DTIs) are a key part of drug development process and their accurate and efficient prediction can significantly boost development efficiency and reduce development time. Recent years have witnessed the rapid advancement of de...

Improved prediction of DNA and RNA binding proteins with deep learning models.

Briefings in bioinformatics
Nucleic acid-binding proteins (NABPs), including DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs), play important roles in essential biological processes. To facilitate functional annotation and accurate prediction of different types of NA...

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

Briefings in bioinformatics
MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure f...

SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.

Briefings in bioinformatics
Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases. However, most genetic and clinical outcome studies are designed in sex-combined framework considering sex as a covariate. Few sex-specific studies h...

A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction.

Briefings in bioinformatics
A major challenge of precision oncology is the identification and prioritization of suitable treatment options based on molecular biomarkers of the considered tumor. In pursuit of this goal, large cancer cell line panels have successfully been studie...

AI Approach for Enhanced Thalassemia Diagnosis Using Blood Smear Images.

Studies in health technology and informatics
This paper aims to propose an approach leveraging Artificial Intelligence (AI) to diagnose thalassemia through medical imaging. The idea is to employ a U-net neural network architecture for precise erythrocyte morphology detection and classification ...

Mutation prediction in the SARS-CoV-2 genome using attention-based neural machine translation.

Mathematical biosciences and engineering : MBE
Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has been evolving rapidly after causing havoc worldwide in 2020. Since then, it has been very hard to contain the virus owing to its frequently mutating nature. Changes in its genome lead t...