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Gene Ontology

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GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data.

Briefings in bioinformatics
Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq ...

SBOannotator: a Python tool for the automated assignment of systems biology ontology terms.

Bioinformatics (Oxford, England)
MOTIVATION: The number and size of computational models in biology have drastically increased over the past years and continue to grow. Modeled networks are becoming more complex, and reconstructing them from the beginning in an exchangeable and repr...

Enhanced disease-disease association with information enriched disease representation.

Mathematical biosciences and engineering : MBE
OBJECTIVE: Quantification of disease-disease association (DDA) enables the understanding of disease relationships for discovering disease progression and finding comorbidity. For effective DDA strength calculation, there is a need to address the main...

PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships.

Bioinformatics (Oxford, England)
MOTIVATION: The rapid accumulation of high-throughput sequence data demands the development of effective and efficient data-driven computational methods to functionally annotate proteins. However, most current approaches used for functional annotatio...

mOWL: Python library for machine learning with biomedical ontologies.

Bioinformatics (Oxford, England)
MOTIVATION: Ontologies contain formal and structured information about a domain and are widely used in bioinformatics for annotation and integration of data. Several methods use ontologies to provide background knowledge in machine learning tasks, wh...

GlycoEnzOnto: a GlycoEnzyme pathway and molecular function ontology.

Bioinformatics (Oxford, England)
MOTIVATION: The 'glycoEnzymes' include a set of proteins having related enzymatic, metabolic, transport, structural and cofactor functions. Currently, there is no established ontology to describe glycoEnzyme properties and to relate them to glycan bi...

Defining the extent of gene function using ROC curvature.

Bioinformatics (Oxford, England)
MOTIVATION: Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specif...

Hierarchical deep learning for predicting GO annotations by integrating protein knowledge.

Bioinformatics (Oxford, England)
MOTIVATION: Experimental testing and manual curation are the most precise ways for assigning Gene Ontology (GO) terms describing protein functions. However, they are expensive, time-consuming and cannot cope with the exponential growth of data genera...

Conditional generative modeling for de novo protein design with hierarchical functions.

Bioinformatics (Oxford, England)
MOTIVATION: Protein design has become increasingly important for medical and biotechnological applications. Because of the complex mechanisms underlying protein formation, the creation of a novel protein requires tedious and time-consuming computatio...

An evidence-based lexical pattern approach for quality assurance of Gene Ontology relations.

Briefings in bioinformatics
Gene Ontology (GO) is widely used in the biological domain. It is the most comprehensive ontology providing formal representation of gene functions (GO concepts) and relations between them. However, unintentional quality defects (e.g. missing or erro...