Genetics

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

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The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning.

Gliomas are primary malignant brain tumors. Monocytes have been proved to actively participate in tu...

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because...

Automatic Search-and-Replace From Examples With Coevolutionary Genetic Programming.

We describe the design and implementation of a system for executing search-and-replace text processi...

Novel application of automated machine learning with MALDI-TOF-MS for rapid high-throughput screening of COVID-19: a proof of concept.

The 2019 novel coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory...

Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has ...

Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus.

Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellf...

Artificial neural network model for predicting changes in ion channel conductance based on cardiac action potential shapes generated via simulation.

Many studies have revealed changes in specific protein channels due to physiological causes such as ...

Improving protein domain classification for third-generation sequencing reads using deep learning.

BACKGROUND: With the development of third-generation sequencing (TGS) technologies, people are able ...

i6mA-VC: A Multi-Classifier Voting Method for the Computational Identification of DNA N6-methyladenine Sites.

DNA N6-methyladenine (6 mA), as an essential component of epigenetic modification, cannot be neglect...

Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning.

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellu...

Ridge regression and its applications in genetic studies.

With the advancement of technology, analysis of large-scale data of gene expression is feasible and ...

Optimal Bayesian Transfer Learning for Count Data.

There is often a limited amount of omics data to design predictive models in biomedicine. Knowing th...

Machine and Deep Learning in Molecular and Genetic Aspects of Sleep Research.

Epidemiological sleep research strives to identify the interactions and causal mechanisms by which s...

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines.

High-throughput screening technologies have provided a large amount of drug sensitivity data for a p...

A Hybrid Supervised Approach to Human Population Identification Using Genomics Data.

Single nucleotide polymorphisms (SNPs) are one type of genetic variations and each SNP represents a ...

Distinguishing between recent balancing selection and incomplete sweep using deep neural networks.

Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Desp...

Prediction of PCR amplification from primer and template sequences using recurrent neural network.

We have developed a novel method to predict the success of PCR amplification for a specific primer s...

High-throughput label-free detection of DNA-to-RNA transcription inhibition using brightfield microscopy and deep neural networks.

Drug discovery is in constant evolution and major advances have led to the development of in vitro h...

Can artificial intelligence overtake human intelligence on the bumpy road towards glioma therapy?

Gliomas are one of the most devastating primary brain tumors which impose significant management cha...

Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.

OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imagi...

HARVESTMAN: a framework for hierarchical feature learning and selection from whole genome sequencing data.

BACKGROUND: Supervised learning from high-throughput sequencing data presents many challenges. For o...

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