Genetics

A machine learning approach for accurate and real-time DNA sequence identification.

BACKGROUND: The all-electronic Single Molecule Break Junction (SMBJ) method is an emerging alternative to traditional polymerase chain reaction (PCR) techniques for genetic sequencing and identification. Existing work indicates that the current spectra recorded from SMBJ experimentations contain unique signatures to identify known sequences from a dataset. However, the spectra are typically extrem...

Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we applied machine learning (ML) to the task of detection of SARS-CoV-2 infection using basic laboratory markers. We performed the statistical analysis and trained an ML model on a retrospective cohort of 5148 patients from 24 hospitals in Hong Kong to cl...

Single-cell classification using graph convolutional networks.

BACKGROUND: Analyzing single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular process...

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans.

COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives of several people. Although potential vaccines are...

An Unbiased Machine Learning Exploration Reveals Gene Sets Predictive of Allograft Tolerance After Kidney Transplantation.

Efforts at finding potential biomarkers of tolerance after kidney transplantation have been hindered by limited sample size, as well as the complicate...

WHISTLE server: A high-accuracy genomic coordinate-based machine learning platform for RNA modification prediction.

The primary sequences of DNA, RNA and protein have been used as the dominant information source of existing machine learning tools, especially for con...

Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine.

The recent deluge of genome-wide technologies for the mapping of the epigenome and resulting data in cancer samples has provided the opportunity for g...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete....

An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism.

Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal ...

InpherNet accelerates monogenic disease diagnosis using patients' candidate genes' neighbors.

PURPOSE: Roughly 70% of suspected Mendelian disease patients remain undiagnosed after genome sequencing, partly because knowledge about pathogenic gen...

Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network.

In the detection of genome variation, the research on the internal correlation of reference genome is deepening; the detection of variation in genome ...

Photonic Crystal Fiber-Based Reconfigurable Biosensor Using Phase Change Material.

A reconfigurable biosensor with different spectral sensitivities could provide new opportunities to increase the label-free selectivity and sensitivit...

Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Combining microfluidics technology with machine learning represents an innovative approach to conduct massive quantitative cell behavior study and imp...

A Deep Learning Approach for Segmentation, Classification, and Visualization of 3-D High-Frequency Ultrasound Images of Mouse Embryos.

Segmentation and mutant classification of high-frequency ultrasound (HFU) mouse embryo brain ventricle (BV) and body images can provide valuable infor...

Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications.

Recent studies suggest that epi-transcriptome regulation via post-transcriptional RNA modifications is vital for all RNA types. Precise identification...

IoU Regression with H+L-Sampling for Accurate Detection Confidence.

It is a common paradigm in object detection frameworks that the samples in training and testing have consistent distributions for the two main tasks: ...

Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach.

Oligonucleotide-based aptamers, which have a three-dimensional structure with a single-stranded fragment, feature various characteristics with respect...

Rapid and sensitive mycoplasma detection system using image-based deep learning.

A major concern in the clinical application of cell therapy is the manufacturing cost of cell products, which mainly depends on quality control. The m...

Characterizing the Clinical Features and Atrophy Patterns of -Related Frontotemporal Dementia With Disease Progression Modeling.

BACKGROUND AND OBJECTIVE: Mutations in the gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signatur...

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a p...