AI Medical Compendium Journal:
BMC bioinformatics

Showing 41 to 50 of 772 articles

MISDP: multi-task fusion visit interval for sequential diagnosis prediction.

BMC bioinformatics
BACKGROUNDS: Diagnostic prediction is a central application that spans various medical specialties and scenarios, sequential diagnosis prediction is the process of predicting future diagnoses based on patients' historical visits. Prior research has u...

Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction.

BMC bioinformatics
The evaluation of drug-gene-disease interactions is key for the identification of drugs effective against disease. However, at present, drugs that are effective against genes that are critical for disease are difficult to identify. Following a diseas...

DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity.

BMC bioinformatics
BACKGROUND: Interactions between microRNAs and RNA-binding proteins are crucial for microRNA-mediated gene regulation and sorting. Despite their significance, the molecular mechanisms governing these interactions remain underexplored, apart from sequ...

NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface.

BMC bioinformatics
BACKGROUND: Vaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens gen...

Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis.

BMC bioinformatics
Antimicrobial peptides (AMPs) are a promising class of antimicrobial drugs due to their broad-spectrum activity against microorganisms. However, their clinical application is limited by their potential to cause hemolysis, the destruction of red blood...

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data.

BMC bioinformatics
BACKGROUND: The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potenti...

Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration.

BMC bioinformatics
BACKGROUND: RNA 5-methyluridine (m5U) modifications play a crucial role in biological processes, making their accurate identification a key focus in computational biology. This paper introduces Deep-m5U, a robust predictor designed to enhance the pre...

Robust double machine learning model with application to omics data.

BMC bioinformatics
BACKGROUND: Recently, there has been a growing interest in combining causal inference with machine learning algorithms. Double machine learning model (DML), as an implementation of this combination, has received widespread attention for their experti...

A mapping-free natural language processing-based technique for sequence search in nanopore long-reads.

BMC bioinformatics
BACKGROUND: In unforeseen situations, such as nuclear power plant's or civilian radiation accidents, there is a need for effective and computationally inexpensive methods to determine the expression level of a selected gene panel, allowing for rough ...

DeepBP: Ensemble deep learning strategy for bioactive peptide prediction.

BMC bioinformatics
BACKGROUND: Bioactive peptides are important bioactive molecules composed of short-chain amino acids that play various crucial roles in the body, such as regulating physiological processes and promoting immune responses and antibacterial effects. Due...