AIMC Topic: Genotype

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Machine Learning Prediction and Experimental Validation of Antigenic Drift in H3 Influenza A Viruses in Swine.

mSphere
The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development of effective vaccines, increasing zoonotic threat and pandemic potential. High-throughput sequencing technologies can quantify IAV genetic diversity,...

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...

High-dimensional hepatopath data analysis by machine learning for predicting HBV-related fibrosis.

Scientific reports
Chronic HBV infection, the main cause of liver cirrhosis and hepatocellular carcinoma, has become a global health concern. Machine learning algorithms are particularly adept at analyzing medical phenomenon by capturing complex and nonlinear relations...

Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

Scientific reports
For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the predictions. Explainability models allow transparency of ML algorithms, however their reliability with...

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in -derived astrocytes ablated mice.

Journal of neurophysiology
Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been ...

Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach.

BioMed research international
PURPOSE: Preoperative prediction of isocitrate dehydrogenase 1 (IDH1) mutation in lower-grade gliomas (LGGs) is crucial for clinical decision-making. This study aimed to examine the predictive value of a machine learning approach using qualitative an...

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Trends in microbiology
The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity w...

Machine learning and statistics to qualify environments through multi-traits in Coffea arabica.

PloS one
Several factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the...

Evolution of drug resistance in HIV protease.

BMC bioinformatics
BACKGROUND: Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques...

Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data.

Journal of plant physiology
Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of the breeding cycle in major crops relevant for sustaining present demands for food, feed, and fuel. In contrast to classical approaches that emphasize the n...