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Gene Ontology

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ProtNote: a multimodal method for protein-function annotation.

Bioinformatics (Oxford, England)
MOTIVATION: Understanding the protein sequence-function relationship is essential for advancing protein biology and engineering. However, <1% of known protein sequences have human-verified functions. While deep-learning methods have demonstrated prom...

GeOKG: geometry-aware knowledge graph embedding for Gene Ontology and genes.

Bioinformatics (Oxford, England)
MOTIVATION: Leveraging deep learning for the representation learning of Gene Ontology (GO) and Gene Ontology Annotation (GOA) holds significant promise for enhancing downstream biological tasks such as protein-protein interaction prediction. Prior ap...

Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.

The plant genome
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underly...

MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.

Bioinformatics (Oxford, England)
MOTIVATION: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models hav...

EnrichDO: a global weighted model for Disease Ontology enrichment analysis.

GigaScience
BACKGROUND: Disease Ontology (DO) has been widely studied in biomedical research and clinical practice to describe the roles of genes. DO enrichment analysis is an effective means to discover associations between genes and diseases. Compared to hundr...

Identification and Immunological Characterization of Cuproptosis Related Genes in Preeclampsia Using Bioinformatics Analysis and Machine Learning.

Journal of clinical hypertension (Greenwich, Conn.)
Preeclampsia (PE) is a pregnancy-specific disorder characterized by an unclearly understood pathogenesis and poses a great threat to maternal and fetal safety. Cuproptosis, a novel form of cellular death, has been implicated in the advancement of var...

scGO: interpretable deep neural network for cell status annotation and disease diagnosis.

Briefings in bioinformatics
Machine learning has emerged as a transformative tool for elucidating cellular heterogeneity in single-cell RNA sequencing. However, a significant challenge lies in the "black box" nature of deep learning models, which obscures the decision-making pr...

Deep learning model for protein multi-label subcellular localization and function prediction based on multi-task collaborative training.

Briefings in bioinformatics
The functional study of proteins is a critical task in modern biology, playing a pivotal role in understanding the mechanisms of pathogenesis, developing new drugs, and discovering novel drug targets. However, existing computational models for subcel...

GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation.

Bioinformatics (Oxford, England)
SUMMARY: The vast majority of proteins still lack experimentally validated functional annotations, which highlights the importance of developing high-performance automated protein function prediction/annotation (AFP) methods. While existing approache...

New GO-based measures in multiple network alignment.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction (PPI) networks provide valuable insights into the function of biological systems. Aligning multiple PPI networks may expose relationships beyond those observable by pairwise comparisons. However, assessing the ...