Genetics

A machine learning approach for rapid early detection of Campylobacter spp. using absorbance spectra collected from enrichment cultures.

Enumeration of Campylobacter from environmental waters can be difficult due to its low concentration...

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.

BACKGROUND: Rifampicin resistant tuberculosis remains a global health problem with almost half a mil...

Diagnostic classification based on DNA methylation profiles using sequential machine learning approaches.

Aberrant methylation patterns in human DNA have great potential for the discovery of novel diagnosti...

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community ...

SeqImprove: Machine-Learning-Assisted Curation of Genetic Circuit Sequence Information.

The progress and utility of synthetic biology is currently hindered by the lengthy process of studyi...

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences.

N-terminal coding sequence (NCS) influences gene expression by impacting the translation initiation ...

Prediction of metabolic syndrome using machine learning approaches based on genetic and nutritional factors: a 14-year prospective-based cohort study.

INTRODUCTION: Metabolic syndrome is a chronic disease associated with multiple comorbidities. Over t...

Identification and validation of oxidative stress-related diagnostic markers for recurrent pregnancy loss: insights from machine learning and molecular analysis.

It has been recognized that oxidative stress (OS) is implicated in the etiology of recurrent pregnan...

m5C-Seq: Machine learning-enhanced profiling of RNA 5-methylcytosine modifications.

Epigenetic modifications, particularly RNA methylation and histone alterations, play a crucial role ...

Probing Nanotopography-Mediated Macrophage Polarization via Integrated Machine Learning and Combinatorial Biophysical Cue Mapping.

Inflammatory responses, leading to fibrosis and potential host rejection, significantly hinder the l...

Joint trajectory inference for single-cell genomics using deep learning with a mixture prior.

Trajectory inference methods are essential for analyzing the developmental paths of cells in single-...

Low-pass whole genome sequencing of circulating tumor cells to evaluate chromosomal instability in triple-negative breast cancer.

Chromosomal Instability (CIN) is a common and evolving feature in breast cancer. Large-scale Transit...

Deciphering colorectal cancer radioresistance and immune microrenvironment: unraveling the role of EIF5A through single-cell RNA sequencing and machine learning.

BACKGROUND: Radiotherapy (RT) is a critical component of treatment for locally advanced rectal cance...

Deep neural networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancer.

MOTIVATION: There exists an unexplained diverse variation within the predefined colon cancer stages ...

MCMVDRP: a multi-channel multi-view deep learning framework for cancer drug response prediction.

Drug therapy remains the primary approach to treating tumours. Variability among cancer patients, in...

Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection.

Utilities face serious obstacles from power theft, which calls for creative ways to maintain income ...

Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: a large-scale pan-cancer cohort, machine learning and experimental study: Retraction.

A commentary on 'Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine-learning'.

Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the...

Inflammatory bowel disease genomics, transcriptomics, proteomics and metagenomics meet artificial intelligence.

Various extrinsic and intrinsic factors such as drug exposures, antibiotic treatments, smoking, life...

SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis.

The integration of morphological attributes extracted from histopathological images and genomic data...