AI Medical Compendium Journal:
BMC bioinformatics

Showing 71 to 80 of 772 articles

SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations.

BMC bioinformatics
BACKGROUND: The potential benefits of drug combination synergy in cancer medicine are significant, yet the risks must be carefully managed due to the possibility of increased toxicity. Although artificial intelligence applications have demonstrated n...

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family.

BMC bioinformatics
PURPOSE: In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is ach...

Hitac: a hierarchical taxonomic classifier for fungal ITS sequences compatible with QIIME2.

BMC bioinformatics
BACKGROUND: Fungi play a key role in several important ecological functions, ranging from organic matter decomposition to symbiotic associations with plants. Moreover, fungi naturally inhabit the human body and can be beneficial when administered as ...

Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets.

BMC bioinformatics
BACKGROUND: Compared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify "unlabeled" samples based on a smaller proportion of known positive examples. This...

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction.

BMC bioinformatics
BACKGROUND: Recognition of enhancer-promoter Interactions (EPIs) is crucial for human development. EPIs in the genome play a key role in regulating transcription. However, experimental approaches for classifying EPIs are too expensive in terms of eff...

A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation.

BMC bioinformatics
BACKGROUND: The exploration of gene-disease associations is crucial for understanding the mechanisms underlying disease onset and progression, with significant implications for prevention and treatment strategies. Advances in high-throughput biotechn...

Equivariant score-based generative diffusion framework for 3D molecules.

BMC bioinformatics
BACKGROUND: Molecular biology is crucial for drug discovery, protein design, and human health. Due to the vastness of the drug-like chemical space, depending on biomedical experts to manually design molecules is exceedingly expensive. Utilizing gener...

PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning.

BMC bioinformatics
BACKGROUND: CAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation is accompanied by the emergence of potentially life-threatening adverse events known as cytokine re...

Multi-class boosting for the analysis of multiple incomplete views on microbiome data.

BMC bioinformatics
BACKGROUND: Microbiome dysbiosis has recently been associated with different diseases and disorders. In this context, machine learning (ML) approaches can be useful either to identify new patterns or learn predictive models. However, data to be fed t...

Machine learning based DNA melt curve profiling enables automated novel genotype detection.

BMC bioinformatics
Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening f...