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Construction and application of Chinese breast cancer knowledge graph based on multi-source heterogeneous data.

Mathematical biosciences and engineering : MBE
The knowledge graph is a critical resource for medical intelligence. The general medical knowledge graph tries to include all diseases and contains much medical knowledge. However, it is challenging to review all the triples manually. Therefore the q...

GPU-accelerated approximate kernel method for quantum machine learning.

The Journal of chemical physics
We introduce Quantum Machine Learning (QML)-Lightning, a PyTorch package containing graphics processing unit (GPU)-accelerated approximate kernel models, which can yield trained models within seconds. QML-Lightning includes a cost-efficient GPU imple...

Utilizing graph machine learning within drug discovery and development.

Briefings in bioinformatics
Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst...

Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.

Briefings in bioinformatics
Accurate predictions of druggability and bioactivities of compounds are desirable to reduce the high cost and time of drug discovery. After more than five decades of continuing developments, quantitative structure-activity relationship (QSAR) methods...

Venn diagrams in bioinformatics.

Briefings in bioinformatics
Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas...

GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.

Briefings in bioinformatics
Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a machine learning techniques-based classification appr...

GPS-Palm: a deep learning-based graphic presentation system for the prediction of S-palmitoylation sites in proteins.

Briefings in bioinformatics
As an important reversible lipid modification, S-palmitoylation mainly occurs at specific cysteine residues in proteins, participates in regulating various biological processes and is associated with human diseases. Besides experimental assays, compu...