Genetics

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical isolates using genomic information and corresponding ...

Cytosine-5 methylation-directed construction of a Au nanoparticle-based nanosensor for simultaneous detection of multiple DNA methyltransferases at the single-molecule level.

DNA methylation at cytosine/guanine dinucleotide islands (CpGIs) is the most prominent epigenetic modification in prokaryotic and eukaryotic genomes. DNA methyltransferases (MTases) are responsible for genomic methylation, and their aberrant activities are closely associated with various diseases including cancers. However, the specific and sensitive detection of multiple DNA MTases has remained a...

Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clea...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin s...

Assessment of and polymorphisms in age-related macular degeneration using classic and machine-learning approaches.

BACKGROUND: and are pivotal genes driving increased risk for age-related macular degeneration (AMD) among several populations. Here, we performed a ...

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions.

The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most ...

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune...

Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning.

High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity ...

Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer.

Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global ...

GeFeS: A generalized wrapper feature selection approach for optimizing classification performance.

In this paper, we propose a generalized wrapper-based feature selection, called GeFeS, which is based on a parallel new intelligent genetic algorithm ...

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network.

Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a d...

Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.

Following prolonged swimming, cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for and here we suggest that in...

Spiking Neural P Systems with Extended Channel Rules.

This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neural P systems with extended channel rules (in short...

Learning machine approach reveals microbial signatures of diet and sex in dog.

The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of h...

A data-driven approach to build a predictive model of cancer patients' disease outcome by utilizing co-expression networks.

BACKGROUND: Next Generation Sequencing (NGS) technologies have revolutionized genomics data research over the last decades by facilitating high-throug...

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies.

Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resistance in prostate cancer (PCa). Identifying mutatio...

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated ...

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods u...

Artificial intelligence powered statistical genetics in biobanks.

Large-scale, sometimes nationwide, prospective genomic cohorts biobanking rich biological specimens such as blood, urine and tissues, have been establ...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis...