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Genetic Diseases, Inborn

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GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease.

Mathematical biosciences and engineering : MBE
For discovery of new usage of drugs, the function type of their target genes plays an important role, and the hypothesis of "Antagonist-GOF" and "Agonist-LOF" has laid a solid foundation for supporting drug repurposing. In this research, an active ge...

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

Genome biology
State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on common disease-associated polymorphisms, yet with modest accuracy and strong positional biases. In this study, we curated 737 high-confidence pathogen...

MMSplice: modular modeling improves the predictions of genetic variant effects on splicing.

Genome biology
Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping prediction challenge. The...

Gene pathogenicity prediction of Mendelian diseases via the random forest algorithm.

Human genetics
The study of Mendelian diseases and the identification of their causative genes are of great significance in the field of genetics. The evaluation of the pathogenicity of genes and the total number of Mendelian disease genes are both important questi...

Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics.

Current protocols in human genetics
The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnost...

Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

PloS one
Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been useful for the prediction of gene essentiality. However, currently available ML pipelines perform poorly ...

Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids
Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible work in bioinformatics. Researchers of various fields are trying to put forth a noninvasive approach to forecast the disease-related genes. As disease...

Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases.

European journal of human genetics : EJHG
Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, lack of proper response to therapies, and absence of valid monitoring tools. We reviewed the relevan...

InpherNet accelerates monogenic disease diagnosis using patients' candidate genes' neighbors.

Genetics in medicine : official journal of the American College of Medical Genetics
PURPOSE: Roughly 70% of suspected Mendelian disease patients remain undiagnosed after genome sequencing, partly because knowledge about pathogenic genes is incomplete and constantly growing. Generating a novel pathogenic gene hypothesis from patient ...