Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning.

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the inte...

A novel based-performance degradation indicator RUL prediction model and its application in rolling bearing.

Aiming at the problem of poor prediction performance of rolling bearing remaining useful life (RUL) ...

A novel end-to-end method to predict RNA secondary structure profile based on bidirectional LSTM and residual neural network.

BACKGROUND: Studies have shown that RNA secondary structure, a planar structure formed by paired bas...

Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.

We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer's Disease (AD) detection a...

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning.

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molec...

Machine learning is the key to diagnose COVID-19: a proof-of-concept study.

The reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coro...

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluabl...

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms und...

Epigenetic Target Fishing with Accurate Machine Learning Models.

Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the ...

Artificial neural networks for multi-omics classifications of hepato-pancreato-biliary cancers: towards the clinical application of genetic data.

PURPOSE: Several multi-omics classifications have been proposed for hepato-pancreato-biliary (HPB) c...

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters.

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs...

Two novel potent ACEI peptides isolated from meat hydrolysates using analysis: identification, screening and inhibitory mechanisms.

The aim of this study was to discover potent angiotensin-converting enzyme (ACE) inhibitory (ACEI) p...

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA.

The prediction of human externally visible characteristics (EVCs) based solely on DNA information ha...

MSA-Regularized Protein Sequence Transformer toward Predicting Genome-Wide Chemical-Protein Interactions: Application to GPCRome Deorphanization.

Small molecules play a critical role in modulating biological systems. Knowledge of chemical-protein...

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects.

Mutational effects predictions continue to improve in accuracy as advanced artificial intelligence (...

Machine learning-based reclassification of germline variants of unknown significance: The RENOVO algorithm.

The increasing scope of genetic testing allowed by next-generation sequencing (NGS) dramatically inc...

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the...

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer.

This study addresses the core issue facing a surgical team during breast cancer surgery: quantitativ...

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