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Gene Ontology

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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...

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...

Screening of the shared pathogenic genes of ulcerative colitis and colorectal cancer by integrated bioinformatics analysis.

Journal of cellular and molecular medicine
Ulcerative colitis (UC) is one of the high-risk pathogenic factors for colorectal cancer (CRC). However, the shared gene and signalling mechanisms between UC and CRC remain unclear. The goal of this study was to delve more into the probable causal re...

Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.

Aging
Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse da...

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...

Self-prediction of relations in GO facilitates its quality auditing.

Journal of biomedical informatics
As applications of the gene ontology (GO) increase rapidly in the biomedical field, quality auditing of it is becoming more and more important. Existing auditing methods are mostly based on rules, observed patterns or hypotheses. In this study, we pr...

Discovering the mechanism of action of drugs with a sparse explainable network.

EBioMedicine
BACKGROUND: Although Deep Neural Networks (DDNs) have been successful in predicting the efficacy of cancer drugs, the lack of explainability in their decision-making process is a significant challenge. Previous research proposed mimicking the Gene On...

HNetGO: protein function prediction via heterogeneous network transformer.

Briefings in bioinformatics
Protein function annotation is one of the most important research topics for revealing the essence of life at molecular level in the post-genome era. Current research shows that integrating multisource data can effectively improve the performance of ...

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 ...