AIMC Topic: Genetic Diseases, Inborn

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

Genetics in medicine : official journal of the American College of Medical Genetics Jul 6, 2021
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 ...
Cohort Studies Knowledge Bases Genetic Diseases, Inborn Humans Machine Learning
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Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

PloS one Nov 30, 2020
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 ...
Humans Machine Learning Area Under Curve Cluster Analysis Algorithms Genes, Essential Genetic Diseases, Inborn Metabolic Networks and Pathways Support Vector Machine
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Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids Jun 22, 2020
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...
Neural Networks, Computer Algorithms Humans Computational Biology Eukaryota DNA Mutation Genetic Diseases, Inborn
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Gene pathogenicity prediction of Mendelian diseases via the random forest algorithm.

Human genetics May 8, 2019
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...
Algorithms ROC Curve Genetic Predisposition to Disease Humans Machine Learning Genes, Recessive Genetic Diseases, Inborn Genes, Dominant
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MMSplice: modular modeling improves the predictions of genetic variant effects on splicing.

Genome biology Mar 1, 2019
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...
Neural Networks, Computer Models, Genetic Genetic Diseases, Inborn Alternative Splicing Genetic Variation
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NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

Genome biology Feb 11, 2019
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...
Genetic Diseases, Inborn DNA, Intergenic Supervised Machine Learning Selection, Genetic Polymorphism, Single Nucleotide Whole Genome Sequencing Humans
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Identifying facial phenotypes of genetic disorders using deep learning.

Nature medicine Jan 7, 2019
Syndromic genetic conditions, in aggregate, affect 8% of the population. Many syndromes have recognizable facial features that are highly informative to clinical geneticists. Recent studies show that facial analysis technologies measured up to the ca...
Humans Algorithms Genetic Diseases, Inborn Image Processing, Computer-Assisted Facies Phenotype Genotype Deep Learning Syndrome
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DES-Mutation: System for Exploring Links of Mutations and Diseases.

Scientific reports Sep 6, 2018
During cellular division DNA replicates and this process is the basis for passing genetic information to the next generation. However, the DNA copy process sometimes produces a copy that is not perfect, that is, one with mutations. The collection of ...
Mutation Knowledge Bases Genetic Diseases, Inborn Humans Software
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Prioritizing Clinically Relevant Copy Number Variation from Genetic Interactions and Gene Function Data.

PloS one Oct 5, 2015
It is becoming increasingly necessary to develop computerized methods for identifying the few disease-causing variants from hundreds discovered in each individual patient. This problem is especially relevant for Copy Number Variants (CNVs), which can...
Congenital Abnormalities Models, Genetic Genetic Predisposition to Disease Gene Dosage Causality Genetic Association Studies Genetic Diseases, Inborn Gene Ontology Genetic Variation Humans Mutation Oligonucleotide Array Sequence Analysis Developmental Disabilities Gene Regulatory Networks
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The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.

American journal of human genetics Jun 25, 2015
The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been ava...
Models, Biological Humans Gene Ontology MEDLINE Phenotype Terminology as Topic Genetic Diseases, Inborn
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