AIMC Topic: Databases, Genetic

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lncRNAfunc: a knowledgebase of lncRNA function in human cancer.

Nucleic acids research
The long non-coding RNAs associating with other molecules can coordinate several physiological processes and their dysfunction can impact diverse human diseases. To date, systematic and intensive annotations on diverse interaction regulations of lncR...

The Human Disease Ontology 2022 update.

Nucleic acids research
The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO's 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on availa...

LncRNAWiki 2.0: a knowledgebase of human long non-coding RNAs with enhanced curation model and database system.

Nucleic acids research
LncRNAWiki, a knowledgebase of human long non-coding RNAs (lncRNAs), has been rapidly expanded by incorporating more experimentally validated lncRNAs. Since it was built based on MediaWiki as its database system, it fails to manage data in a structur...

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Bioscience reports
BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patien...

scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network.

Nucleic acids research
Advances in single-cell RNA sequencing (scRNA-seq) have furthered the simultaneous classification of thousands of cells in a single assay based on transcriptome profiling. In most analysis protocols, single-cell type annotation relies on marker genes...

Construction of a 5-feature gene model by support vector machine for classifying osteoporosis samples.

Bioengineered
Osteoporosis is a progressive bone disease in the elderly and lacks an effective classification method of patients. This study constructed a gene signature for an accurate prediction and classification of osteoporosis patients. Three gene expression ...

A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics.

Bioengineered
Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected...

PreTP-EL: prediction of therapeutic peptides based on ensemble learning.

Briefings in bioinformatics
Therapeutic peptides are important for understanding the correlation between peptides and their therapeutic diagnostic potential. The therapeutic peptides can be further divided into different types based on therapeutic function sharing different cha...

Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Briefings in bioinformatics
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is ...