Genetics

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understanding gene expression patterns. While there are many attempts to develop computational promoter and enhancer identification methods, reliable tools to ...

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid t...

In utero exposure to electronic-cigarette aerosols decreases lung fibrillar collagen content, increases Newtonian resistance and induces sex-specific molecular signatures in neonatal mice.

Approximately 7% of pregnant women in the United States use electronic-cigarette (e-cig) devices during pregnancy. There is, however, no scientific ev...

NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the ...

Multitrait machine- and deep-learning models for genomic selection using spectral information in a wheat breeding program.

Prediction of breeding values is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine- and ...

Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extens...

rBPDL:Predicting RNA-Binding Proteins Using Deep Learning.

RNA-binding protein (RBP) is a powerful and wide-ranging regulator that plays an important role in cell development, differentiation, metabolism, heal...

Chemometric quality assessment of Paracetamol and Phenylephrine Hydrochloride with Paracetamol impurities; comparative UV-spectrophotometric implementation of four predictive models.

Spectrophotometric data analysis using multivariate approaches has many useful applications. One of these applications is the analysis of active ingre...

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological ...

Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study.

BACKGROUND: Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic sc...

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.

Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bact...

Identification of Autistic Risk Candidate Genes and Toxic Chemicals via Multilabel Learning.

As a group of complex neurodevelopmental disorders, autism spectrum disorder (ASD) has been reported to have a high overall prevalence, showing an unp...

Chemotherapeutic potential of Cayratia trifolia L nhexane extract on A2780 cells.

It is of interest to report the chemotherapeutic (drug target based) potential of n-hexane Cayratia trifolia L. (C.trifolia) extract on A2780 cell lin...

English Feature Recognition Based on GA-BP Neural Network Algorithm and Data Mining.

With the development of society and the promotion of science and technology, English, as the largest universal language in the world, is used by more ...

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by thi...

A Deep Learning-Enabled Electrocardiogram Model for the Identification of a Rare Inherited Arrhythmia: Brugada Syndrome.

BACKGROUND: Brugada syndrome is a major cause of sudden cardiac death in young people and has distinctive electrocardiographic (ECG) features. We aime...

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.

BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a si...

Gene Ontology representation for transcription factor functions.

Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular env...

Predicting phenotypes from genetic, environment, management, and historical data using CNNs.

Convolutional Neural Networks (CNNs) can perform similarly or better than standard genomic prediction methods when sufficient genetic, environmental, ...

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The curren...