Genetics

Prediction of protein-ligand binding affinity from sequencing data with interpretable machine learning.

Protein-ligand interactions are increasingly profiled at high throughput using affinity selection an...

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized b...

Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning.

Despite the fact that the cell cycle is a fundamental process of life, a detailed quantitative under...

Identification of DNA N4-methylcytosine sites based on multi-source features and gradient boosting decision tree.

N4-methylcytosine (4 mC) is an important and common methylation which widely exists in prokaryotes. ...

Prediction of nucleosome dynamic interval based on long-short-term memory network (LSTM).

Nucleosome localization is a dynamic process and consists of nucleosome dynamic intervals (NDIs). We...

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatm...

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches.

An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was repor...

Automatic recognition of micronucleus by combining attention mechanism and AlexNet.

BACKGROUND: Micronucleus (MN) is an abnormal fragment in a human cell caused by disorders in the mec...

Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growi...

Learning deep neural networks' architectures using differential evolution. Case study: Medical imaging processing.

The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care la...

Editorial for "A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Prediction of KRAS Mutation in Rectal Cancer".

Advances in Designer DNA Nanorobots Enabling Programmable Functions.

The advent of DNA nanotechnology has paved the way for the development of nanoscale robotics capable...

Machine learning sequence prioritization for cell type-specific enhancer design.

Recent discoveries of extreme cellular diversity in the brain warrant rapid development of technolog...

Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis.

PURPOSE: The study aimed to determine the diagnostic yield, optimal timing, and methodology of next ...

DNA Memristors and Their Application to Reservoir Computing.

This paper introduces memristors realized by molecular and DNA reactions. Molecular memristors proce...

Cross-tissue immune cell analysis reveals tissue-specific features in humans.

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues...

Prediction of lung cancer using gene expression and deep learning with KL divergence gene selection.

BACKGROUND: Lung cancer is one of the cancers with the highest mortality rate in China. With the rap...

The future of artificial intelligence in digital pathology - results of a survey across stakeholder groups.

AIMS: Artificial intelligence (AI) provides a powerful tool to extract information from digitised hi...

Deep learning of a bacterial and archaeal universal language of life enables transfer learning and illuminates microbial dark matter.

The majority of microbial genomes have yet to be cultured, and most proteins identified in microbial...

Molecular archaeology and machine learning: Deep learning algorithms help to uncover ancient genes in our genomes and their evolutionary role: Deep learning algorithms help to uncover ancient genes in our genomes and their evolutionary role.

The study of ancient genes in contemporary species is providing new insights about how organisms ada...

Compare the performance of multiple binary classification models in microbial high-throughput sequencing datasets.

The development of machine learning and deep learning provided solutions for predicting microbiota r...