AI Medical Compendium Topic:
Mutation

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Machine learning application for patient stratification and phenotype/genotype investigation in a rare disease.

Briefings in bioinformatics
Alkaptonuria (AKU, OMIM: 203500) is an autosomal recessive disorder caused by mutations in the Homogentisate 1,2-dioxygenase (HGD) gene. A lack of standardized data, information and methodologies to assess disease severity and progression represents ...

Radiogenomic and Deep Learning Network Approaches to Predict Mutation from Radiotherapy Plan CT.

Anticancer research
BACKGROUND/AIM: We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using radiotherapy planning computed tomography (CT) images in patients with locally advanced rectal cance...

DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network.

Briefings in bioinformatics
It is of considerable interest to detect somatic mutations in paired tumor and normal sequencing data. A number of callers that are based on statistical or machine learning approaches have been developed to detect somatic small variants. However, the...

Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...

Deep representation learning improves prediction of LacI-mediated transcriptional repression.

Proceedings of the National Academy of Sciences of the United States of America
Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of ...

A novel machine learning approach (svmSomatic) to distinguish somatic and germline mutations using next-generation sequencing data.

Zoological research
Somatic mutations are a large category of genetic variations, which play an essential role in tumorigenesis. Detection of somatic single nucleotide variants (SNVs) could facilitate downstream analysis of tumorigenesis. Many computational methods have...

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Proceedings of the National Academy of Sciences of the United States of America
Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer gen...

An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-co...