Semantic similarity and machine learning with ontologies
Ontologies have long been employed in the life sciences to formally represent and reason
over domain knowledge and they are employed in almost every major biological database …
over domain knowledge and they are employed in almost every major biological database …
Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion
Protein function prediction is an essential task in bioinformatics which benefits disease
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in …
Computational methods for prediction of human protein-phenotype associations: a review
Deciphering the relationship between human proteins (genes) and phenotypes is one of the
fundamental tasks in phenomics research. The Human Phenotype Ontology (HPO) builds …
fundamental tasks in phenomics research. The Human Phenotype Ontology (HPO) builds …
DeepViral: prediction of novel virus–host interactions from protein sequences and infectious disease phenotypes
Motivation Infectious diseases caused by novel viruses have become a major public health
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
SSLpheno: a self-supervised learning approach for gene–phenotype association prediction using protein–protein interactions and gene ontology data
X Bi, W Liang, Q Zhao, J Wang - Bioinformatics, 2023 - academic.oup.com
Motivation Medical genomics faces significant challenges in interpreting disease phenotype
and genetic heterogeneity. Despite the establishment of standardized disease phenotype …
and genetic heterogeneity. Despite the establishment of standardized disease phenotype …
Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
Motivation Whole-exome and genome sequencing have become common tools in
diagnosing patients with rare diseases. Despite their success, this approach leaves many …
diagnosing patients with rare diseases. Despite their success, this approach leaves many …
Breaking bad news in the era of artificial intelligence and algorithmic medicine: an exploration of disclosure and its ethical justification using the hedonic calculus
An appropriate ethical framework around the use of Artificial Intelligence (AI) in healthcare
has become a key desirable with the increasingly widespread deployment of this …
has become a key desirable with the increasingly widespread deployment of this …
Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches
The taxonomic structure of microbial community sample is highly habitat-specific, making
source tracking possible, allowing identification of the niches where samples originate …
source tracking possible, allowing identification of the niches where samples originate …
DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning
Motivation Structural genomic variants account for much of human variability and are
involved in several diseases. Structural variants are complex and may affect coding regions …
involved in several diseases. Structural variants are complex and may affect coding regions …
Ontology-Based decision tree model for prediction of fatty liver diseases
SY Banihashem, S Shishehchi - Computer Methods in …, 2023 - Taylor & Francis
Abstract Non-Alcohol Fatty liver disease is a common clinical complication. The paper aimed
to develop a knowledge-based fatty liver detection system based on an ontology and …
to develop a knowledge-based fatty liver detection system based on an ontology and …