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Databases, Genetic

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Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.

Scientific reports
Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis - the ontolo...

Disease Ontology: improving and unifying disease annotations across species.

Disease models & mechanisms
Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontol...

Phylogenetic convolutional neural networks in metagenomics.

BMC bioinformatics
BACKGROUND: Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architectu...

Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Translational psychiatry
Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have resulted in an ever-growing list of ASD candidate genes. However, only a fraction of the hundreds of nomin...

Exploring autophagy with Gene Ontology.

Autophagy
Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular ...

Using OWL reasoning to support the generation of novel gene sets for enrichment analysis.

Journal of biomedical semantics
BACKGROUND: The Gene Ontology (GO) consists of over 40,000 terms for biological processes, cell components and gene product activities linked into a graph structure by over 90,000 relationships. It has been used to annotate the functions and cellular...

Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways.

Scientific reports
The war on cancer is progressing globally but slowly as researchers around the world continue to seek and discover more innovative and effective ways of curing this catastrophic disease. Organizing biological information, representing it, and making ...

Support vector machine classifier for prediction of the metastasis of colorectal cancer.

International journal of molecular medicine
Colorectal cancer (CRC) is one of the most common cancers and a major cause of mortality. The present study aimed to identify potential biomarkers for CRC metastasis and uncover the mechanisms underlying the etiology of the disease. The five datasets...

Improved ontology for eukaryotic single-exon coding sequences in biological databases.

Database : the journal of biological databases and curation
Efficient extraction of knowledge from biological data requires the development of structured vocabularies to unambiguously define biological terms. This paper proposes descriptions and definitions to disambiguate the term 'single-exon gene'. Eukaryo...