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Genetic Loci

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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...

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...

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 ...

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...

Epistasis Detection Based on Epi-GTBN.

Methods in molecular biology (Clifton, N.J.)
Epistasis detection is a hot topic in bioinformatics due to its relevance to the detection of specific phenotypic traits and gene-gene interactions. Here, we present a step-by-step protocol to apply Epi-GTBN, a machine learning-based method based on ...

iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.

Briefings in bioinformatics
DNase I hypersensitive site (DHS) refers to the hypersensitive region of chromatin for the DNase I enzyme. It is an important part of the noncoding region and contains a variety of regulatory elements, such as promoter, enhancer, and transcription fa...

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...

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...

Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches.

Combinatorial chemistry & high throughput screening
INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting asthma using machine-learning approaches.

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...