Genetics

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.

Genomic prediction plays an increasingly important role in modern animal breeding, with predictive a...

Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.

Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can le...

DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.

Orofacial clefts (OFCs) are among the most common human congenital birth defects. Previous multiethn...

Development and validation of a reliable DNA copy-number-based machine learning algorithm (CopyClust) for breast cancer integrative cluster classification.

The Integrative Cluster subtypes (IntClusts) provide a framework for the classification of breast ca...

Advancing automatic text summarization: Unleashing enhanced binary multi-objective grey wolf optimization with mutation.

Automatic Text Summarization (ATS) is gaining popularity as there is a growing demand for a system c...

Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models.

The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has...

An interpretable data-driven prediction model to anticipate scoliosis in spinal muscular atrophy in the era of (gene-) therapies.

5q-spinal muscular atrophy (SMA) is a neuromuscular disorder (NMD) that has become one of the first ...

Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients.

BACKGROUND: Prospective observational studies have demonstrated that the machine learning (ML) -guid...

Prediction of Protein-DNA Interface Hot Spots Based on Empirical Mode Decomposition and Machine Learning.

Protein-DNA complex interactivity plays a crucial role in biological activities such as gene express...

Development of a two-layer machine learning model for the forensic application of legal and illegal poppy classification based on sequence data.

Poppies are beneficial plants with a variety of applications, including medicinal, edible, ornamenta...

Characterization of PANoptosis-related genes in Crohn's disease by integrated bioinformatics, machine learning and experiments.

Currently, the biological understanding of Crohn's disease (CD) remains limited. PANoptosis is a rev...

Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models.

When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mut...

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods.

Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in a...

Residual networks without pooling layers improve the accuracy of genomic predictions.

Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its pred...

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Increased left atrial volume and decreased left atrial function have long been associated with atria...

Stacked neural network for predicting polygenic risk score.

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility fr...

BiLSTM- and CNN-Based m6A Modification Prediction Model for circRNAs.

m6A methylation, a ubiquitous modification on circRNAs, exerts a profound influence on RNA function,...

Fragmentomics features of ovarian cancer.

Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset...

A Fusion Learning Model Based on Deep Learning for Single-Cell RNA Sequencing Data Clustering.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the diseas...

A novel support vector machine-based 1-day, single-dose prediction model of genotoxic hepatocarcinogenicity in rats.

The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity o...