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Alleles

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Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PloS one
Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biolog...

Prediction of feature genes in trauma patients with the TNF rs1800629 A allele using support vector machine.

Computers in biology and medicine
BACKGROUND: Tumor necrosis factor (TNF)-α variant is closely linked to sepsis syndrome and mortality after severe trauma. We aimed to identify feature genes associated with the TNF rs1800629 A allele in trauma patients and help to direct them toward ...

Machine learning to optimize automated RH genotyping using whole-exome sequencing data.

Blood advances
Rh phenotype matching reduces but does not eliminate alloimmunization in patients with sickle cell disease (SCD) due to RH genetic diversity that is not distinguishable by serological typing. RH genotype matching can potentially mitigate Rh alloimmun...

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Methods in molecular biology (Clifton, N.J.)
Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputatio...

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The APOE-ε4 allele is a known genetic risk for Alzheimer's disease (AD). Thus, it can be reasoned that the APOE-ε4 allele would also impact neurodegeneration-associated structural brain changes. Here we probe if the APOE-ε4 genotype directly modulate...

Identification of haploinsufficient genes from epigenomic data using deep forest.

Briefings in bioinformatics
Haploinsufficiency, wherein a single allele is not enough to maintain normal functions, can lead to many diseases including cancers and neurodevelopmental disorders. Recently, computational methods for identifying haploinsufficiency have been develop...

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

Journal of Alzheimer's disease : JAD
BACKGROUND: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET ima...

Graphical classification of DNA sequences of HLA alleles by deep learning.

Human cell
Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence "Deep Learning (Stacked autoencoder)". Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno...

Interaction between SELP genetic polymorphisms with inflammatory cytokine interleukin-6 (IL-6) gene variants on cardiovascular disease in Chinese Han population.

Mammalian genome : official journal of the International Mammalian Genome Society
The aim of the study is to investigate the impact of SELP and IL-6 genetic single-nucleotide polymorphisms (SNPs) and its gene-gene interaction on cardiovascular disease (CVD) risk based on Chinese population. A total of 1082 subjects (519 males, 563...

An artificial neural network system to identify alleles in reference electropherograms.

Forensic science international. Genetics
Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data t...