AIMC Topic: Genetic Loci

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Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Nature communications
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to asse...

Machine Learning to Advance Human Genome-Wide Association Studies.

Genes
Machine learning, including deep learning, reinforcement learning, and generative artificial intelligence are revolutionising every area of our lives when data are made available. With the help of these methods, we can decipher information from large...

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

Nature genetics
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a quantitative liability score has more power...

The mining and construction of a knowledge base for gene-disease association in mitochondrial diseases.

Scientific reports
Mitochondrial diseases are a group of heterogeneous genetic metabolic diseases caused by mitochondrial DNA (mtDNA) or nuclear DNA (nDNA) gene mutations. Mining the gene-disease association of mitochondrial diseases is helpful for understanding the pa...

The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.

Frontiers in endocrinology
Musculoskeletal research has been enriched in the past ten years with a great wealth of new discoveries arising from genome wide association studies (GWAS). In addition to the novel factors identified by GWAS, the advent of whole-genome and whole-exo...

DeepciRGO: functional prediction of circular RNAs through hierarchical deep neural networks using heterogeneous network features.

BMC bioinformatics
BACKGROUND: Circular RNAs (circRNAs) are special noncoding RNA molecules with closed loop structures. Compared with the traditional linear RNA, circRNA is more stable and not easily degraded. Many studies have shown that circRNAs are involved in the ...

Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.

Genomics
Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miR...

DualWMDR: Detecting epistatic interaction with dual screening and multifactor dimensionality reduction.

Human mutation
Detecting epistatic interaction is a typical way of identifying the genetic susceptibility of complex diseases. Multifactor dimensionality reduction (MDR) is a decent solution for epistasis detection. Existing MDR-based methods still suffer from high...

Forensic STR allele extraction using a machine learning paradigm.

Forensic science international. Genetics
We present a machine learning approach to short tandem repeat (STR) sequence detection and extraction from massively parallel sequencing data called Fragsifier. Using this approach, STRs are detected on each read by first locating the longest repeat ...

PBMDR: A particle swarm optimization-based multifactor dimensionality reduction for the detection of multilocus interactions.

Journal of theoretical biology
Studies on multilocus interactions have mainly investigated the associations between genetic variations from the related genes and histopathological tumor characteristics in patients. However, currently, the identification and characterization of sus...