Genetics

A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID-19 Cases from Chest X-Ray Images.

. The new coronavirus disease (known as COVID-19) was first identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and people's everyday lives. As the number of COVID-19 cases is rapidly increasing, a reliable detection technique is needed to identify affected individuals and care for them in the early stages of COVID-19 and reduce the virus's transmission. The most access...

Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.

To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one prior pregnancy. HHV-6 DNA was discovered in both infertile and fertile peripheral blood mononuclear cells (PBMC) (12 and 14%, respectively); endometrial epithelial cells from 4/10 (40%) infertile women were positive for HHV-6 DNA; this viral DNA was ...

Deep-Learning-Based Cancer Profiles Classification Using Gene Expression Data Profile.

The quantity of data required to give a valid analysis grows exponentially as machine learning dimensionality increases. In a single experiment, micro...

PanClassif: Improving pan cancer classification of single cell RNA-seq gene expression data using machine learning.

Cancer is one of the major causes of human death per year. In recent years, cancer identification and classification using machine learning have gaine...

Extendable and explainable deep learning for pan-cancer radiogenomics research.

Radiogenomics is a field where medical images and genomic profiles are jointly analyzed to answer critical clinical questions. Specifically, people wa...

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning.

BACKGROUND: A limitation of traditional differential expression analysis on small datasets involves the possibility of false positives and false negat...

Deep Unfolding for Non-Negative Matrix Factorization with Application to Mutational Signature Analysis.

Non-negative matrix factorization (NMF) is a fundamental matrix decomposition technique that is used primarily for dimensionality reduction and is inc...

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data.

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting...

Deep RED Unfolding Network for Image Restoration.

The deep unfolding network (DUN) provides an efficient framework for image restoration. It consists of a regularization module and a data fitting modu...

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer...

An RNA-based theory of natural universal computation.

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet w...

RegVar: Tissue-specific Prioritization of Non-coding Regulatory Variants.

Non-coding genomic variants constitute the majority of trait-associated genome variations; however, the identification of functional non-coding varian...

Tungsten oxide polymorphs and their multifunctional applications.

Owing to the natural abundance, easy availability, high stability, non-stoichiometry, and chemical diversity, considerable interest has been devoted t...

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.

Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independe...

DNA-based artificial dendritic cells for in situ cytotoxic T cell stimulation and immunotherapy.

In immunotherapy, ex vivo stimulation of T cells requires significant resources and effort. Here, we report artificial dendritic cell-mimicking DNA mi...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosy...

NoAS-DS: Neural optimal architecture search for detection of diverse DNA signals.

Neural network architectures are high-performing variable models that can solve many learning tasks. Designing architectures manually require substant...

Manipulation of Multiple Cell-Cell Interactions by Tunable DNA Scaffold Networks.

Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. Howe...

NGS read classification using AI.

Clinical metagenomics is a powerful diagnostic tool, as it offers an open view into all DNA in a patient's sample. This allows the detection of pathog...

Combination of liquid crystal and deep learning reveals distinct signatures of Parkinson's disease-related wild-type α-synuclein and six pathogenic mutants.

α-Synuclein is a central player in Parkinson's disease (PD) pathology. Various point mutations in α-synuclein have been identified to alter the protei...