Genetics

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

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Constructing a Consciousness Meter Based on the Combination of Non-Linear Measurements and Genetic Algorithm-Based Support Vector Machine.

OBJECTIVE: Constructing a framework to evaluate consciousness is an important issue in neuroscience ...

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

PURPOSE: Tumor genomic features have been of particular interest because of their potential impact o...

Gait characteristics and clinical relevance of hereditary spinocerebellar ataxia on deep learning.

BACKGROUND: Deep learning has always been at the forefront of scientific research. It has also been ...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade thera...

R/PY-SUMMA: An R/Python Package for Unsupervised Ensemble Learning for Binary Classification Problems in Bioinformatics.

The increasing availability of complex data in biology and medicine has promoted the use of machine ...

Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes.

Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmos...

Polymorphism Is Associated with Impaired Oral Clearance of Gliclazide in Healthy Chinese.

BACKGROUND: Previous studies suggest gliclazide is metabolised primarily by CYP2C19 rather than CYP2...

DNA is not an ontologically distinctive developmental cause.

In this article I critically evaluate the thesis that DNA is an ontologically distinctive developmen...

The sweet detection of rolling circle amplification: Glucose-based electrochemical genosensor for the detection of viral nucleic acid.

Herein, an isothermal padlock probe-based assay for the simple and portable detection of pathogens c...

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

In many research areas scientists are interested in clustering objects within small datasets while m...

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predi...

iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.

BACKGROUND: Since protein-DNA interactions are highly essential to diverse biological events, accura...

iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks.

BACKGROUND: Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transc...

JCDB: a comprehensive knowledge base for Jatropha curcas, an emerging model for woody energy plants.

BACKGROUND: Jatropha curcas is an oil-bearing plant, and has seeds with high oil content (~ 40%). Se...

Predicting RNA secondary structure via adaptive deep recurrent neural networks with energy-based filter.

BACKGROUND: RNA secondary structure prediction is an important issue in structural bioinformatics, a...

Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets.

Many clinical studies have revealed the high biological similarities existing among different skin p...

A tri-functional probe mediated exponential amplification strategy for highly sensitive detection of Dnmt1 and UDG activities at single-cell level.

Multiplex DNA methylation and glycosylation are ubiquitous in the human body to ensure the normal fu...

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