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Genetic Predisposition to Disease

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A Fast Linear Neighborhood Similarity-Based Network Link Inference Method to Predict MicroRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
Increasing evidences revealed that microRNAs (miRNAs) play critical roles in important biological processes. The identification of disease-related miRNAs is critical to understand the molecular mechanisms of human diseases. Most existing computationa...

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes.

Nature communications
Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce the reliability of trans-ethnic major histocompatibility complex (MHC) fine-mapping due to inter-ethn...

MVP predicts the pathogenicity of missense variants by deep learning.

Nature communications
Accurate pathogenicity prediction of missense variants is critically important in genetic studies and clinical diagnosis. Previously published prediction methods have facilitated the interpretation of missense variants but have limited performance. H...

Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

International journal of molecular sciences
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.

PLoS computational biology
Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted...

Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.

Aging
Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To find susceptibility genes and develop a novel predictive model of ulcerative colitis, two sets of c...

Precision Medicine, AI, and the Future of Personalized Health Care.

Clinical and translational science
The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less-common responses to treatment or unique healthcare needs. AI leverages ...

Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Journal of human genetics
Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A de...

Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma.

Virchows Archiv : an international journal of pathology
In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slide...

Evaluating the informativeness of deep learning annotations for human complex diseases.

Nature communications
Deep learning models have shown great promise in predicting regulatory effects from DNA sequence, but their informativeness for human complex diseases is not fully understood. Here, we evaluate genome-wide SNP annotations from two previous deep learn...