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Genetic Predisposition to Disease

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Machine Learning Approaches for the Prioritization of Genomic Variants Impacting Pre-mRNA Splicing.

Cells
Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient's variant landscape, the ability to characterize variants causing splicing defects ha...

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...

Genetic Variation in Cytochrome P450 2R1 and Vitamin D Binding Protein Genes are associated with Vitamin D Deficiency in Adolescents.

International journal for vitamin and nutrition research. Internationale Zeitschrift fur Vitamin- und Ernahrungsforschung. Journal international de vitaminologie et de nutrition
Genome Wide Association Studies (GWAS) have evaluated several genes related to vitamin D synthesis, metabolism and transport. They have proposed a genetic basis for low levels of vitamin D in the blood. The current study aims to investigate the rela...

LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.

International journal of molecular sciences
Long non-coding RNAs (lncRNAs) play a crucial role in the pathogenesis and development of complex diseases. Predicting potential lncRNA-disease associations can improve our understanding of the molecular mechanisms of human diseases and help identify...

Prediction of Potential miRNA-Disease Associations Through a Novel Unsupervised Deep Learning Framework with Variational Autoencoder.

Cells
The important role of microRNAs (miRNAs) in the formation, development, diagnosis, and treatment of diseases has attracted much attention among researchers recently. In this study, we present an unsupervised deep learning model of the variational aut...

LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring.

IEEE journal of biomedical and health informatics
There is much evidence that long non-coding RNA (lncRNA) is associated with many diseases. However, it is time-consuming and expensive to identify meaningful lncRNA-disease associations (LDAs) through medical or biological experiments. Therefore, inv...

Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.

International journal of molecular sciences
Identification of disease-associated miRNAs (disease miRNAs) are critical for understanding etiology and pathogenesis. Most previous methods focus on integrating similarities and associating information contained in heterogeneous miRNA-disease networ...

Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases.

Artificial intelligence in medicine
In order to gain insight into oligogenic disorders, understanding those involving bi-locus variant combinations appears to be key. In prior work, we showed that features at multiple biological scales can already be used to discriminate among two type...

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.

Scientific reports
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machin...