Genetics

Artificial intelligence applications for oncological positron emission tomography imaging.

Positron emission tomography (PET), a functional and dynamic molecular imaging technique, is generally used to reveal tumors' biological behavior. Radiomics allows a high-throughput extraction of multiple features from images with artificial intelligence (AI) approaches and develops rapidly worldwide. Quantitative and objective features of medical images have been explored to recognize reliable bi...

DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks.

Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate the enumeration process, we develop a chromosome enumeration framework, DeepACEv2, based on the region based object detection scheme. The framework is developed following three steps. Firstly, we take the classical ResNet-101 as the backbone and attach the Feature Pyramid Network (FPN) to the backbone...

Identifying longevity associated genes by integrating gene expression and curated annotations.

Aging is a complex process with poorly understood genetic mechanisms. Recent studies have sought to classify genes as pro-longevity or anti-longevity ...

Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks.

Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and ...

Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been usefu...

A machine learning framework for the prediction of chromatin folding in using epigenetic features.

Technological advances have lead to the creation of large epigenetic datasets, including information about DNA binding proteins and DNA spatial struct...

Extraction of the molecular level biomedical event trigger based on gene ontology using radial belief neural network techniques.

Detection of molecular level biomedical event extraction plays a vital role in creating and visualizing the applications related to natural language p...

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification.

Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their impo...

Surveillance of SARS-CoV-2 in sewage and wastewater treatment plants in Mexico.

The SARS-CoV-2 virus causing COVID-19 is spread in sewage by the stool of infected individuals, and viral material in sewage can be quantified using m...

A Rare Case of Familial Neurogenic Diabetes Insipidus in a 22-Year-Old Man.

OBJECTIVE: Diabetes insipidus (DI) can be classified into 2 types: central/neurogenic DI and nephrogenic DI. Most cases of central DI occur after brai...

Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging.

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastro...

Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images.

OBJECTIVES: The high variability of hypertrophic cardiomyopathy (HCM) genetic phenotypes has prompted the establishment of risk-stratification systems...

Intractable airsickness associated with COVID-19: A case report.

A 29-yr-old male Melicopter co-pilot with high flight hours in air transport missions of the patients with COVID-19 tested positive for his RT-PCR due...

Identifying transcriptomic correlates of histology using deep learning.

Linking phenotypes to specific gene expression profiles is an extremely important problem in biology, which has been approached mainly by correlation ...

Artificial intelligence to predict the BRAFV600E mutation in patients with thyroid cancer.

PURPOSE: To investigate whether a computer-aided diagnosis (CAD) program developed using the deep learning convolutional neural network (CNN) on neck ...

Facial Expression Recognition Using Frequency Neural Network.

Facial expression recognition has become a newly-emerging topic in recent decades, which has important value in the field of human-computer interactio...

Transforming the study of organisms: Phenomic data models and knowledge bases.

The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model org...

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious d...

Identification of contributing genes of Huntington's disease by machine learning.

BACKGROUND: Huntington's disease (HD) is an inherited disorder caused by the polyglutamine (poly-Q) mutations of the HTT gene results in neurodegenera...

Cnngeno: A high-precision deep learning based strategy for the calling of structural variation genotype.

Genotype plays a significant role in determining characteristics in an organism and genotype calling has been greatly accelerated by sequencing techno...