AIMC Topic: DNA, Mitochondrial

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Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.

Cardiovascular diabetology Jun 11, 2019
BACKGROUND: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are two to four times more likely to develop cardiovascular diseases. While HbA1c remains the primary dia...
DNA Methylation Glycated Hemoglobin Genetic Markers Models, Genetic Support Vector Machine Systems Integration Mitochondria, Heart Diabetic Cardiomyopathies DNA, Mitochondrial CpG Islands Diabetes Mellitus, Type 2 Genomics Polymorphism, Single Nucleotide Epigenesis, Genetic Genetic Predisposition to Disease Risk Assessment Disease Progression Male Middle Aged Humans Female Risk Factors Prognosis
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A single nucleotide polymorphism panel for individual identification and ancestry assignment in Caucasians and four East and Southeast Asian populations using a machine learning classifier.

Forensic science, medicine, and pathology Jan 16, 2019
Single nucleotide polymorphism (SNP) profiling is an effective means of individual identification and ancestry inferences in forensic genetics. This study established a SNP panel for the simultaneous individual identification and ancestry assignment ...
Support Vector Machine DNA, Mitochondrial White People Gene Frequency Asian People Polymorphism, Single Nucleotide Genotype DNA Degradation, Necrotic Female Humans Genetics, Population Male Asia DNA Fingerprinting Machine Learning Chromosomes, Human, Y Retrospective Studies Chromosomes, Human, X
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Machine learning classifier for identification of damaging missense mutations exclusive to human mitochondrial DNA-encoded polypeptides.

BMC bioinformatics Mar 7, 2017
BACKGROUND: Several methods have been developed to predict the pathogenicity of missense mutations but none has been specifically designed for classification of variants in mtDNA-encoded polypeptides. Moreover, there is not available curated dataset ...
Computational Biology Humans DNA, Mitochondrial Machine Learning Mitochondria Sensitivity and Specificity DNA Mutational Analysis Peptides Mutation, Missense
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Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes.

World journal of gastroenterology Mar 14, 2025
BACKGROUND: Insulin resistance, lipotoxicity, and mitochondrial dysfunction contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD). Mitochondrial dysfunction impairs oxidative phosphorylation and increases ...
Cohort Studies Adult Polymorphism, Single Nucleotide DNA, Mitochondrial Random Forest Male Logistic Models Diabetes Complications Non-alcoholic Fatty Liver Disease Humans Middle Aged Boosting Machine Learning Algorithms Case-Control Studies
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Adaptive sequencing using nanopores and deep learning of mitochondrial DNA.

Briefings in bioinformatics Jul 18, 2022
Nanopore sequencing is an emerging technology that reads DNA by utilizing a unique method of detecting nucleic acid sequences and identifies the various chemical modifications they carry. Deep learning has increased in popularity as a useful techniqu...
High-Throughput Nucleotide Sequencing Nanopores Sequence Analysis, DNA DNA, Mitochondrial Humans Deep Learning
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[Variability of Cytochrome b Gene and Adjacent Section of Gene tRNA-Thr of Mitochondrial DNA in the Northern Mole Vole Ellobius talpinus (Mammalia, Rodentia)].

Genetika Dec 1, 2015
The Northern mole vole E. talpinus, despite its wide distribution, is characterized by a stable karyotype (2n = NF = 54) and slight morphological polymorphism. We made a preliminary analysis of a mitochondrial DNA fragment to clarify the level of gen...
Arvicolinae Cytochromes b DNA, Mitochondrial RNA, Transfer, Thr Genetic Variation Animals Male
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