Genetics

Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.

Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious disease involving intricate immunological molecules, diverse signaling pathways, and multifaceted immune processes. N6-methyladenosine (m6A), a critical epigenetic modification, regulates various immune-metabolic and pathological pathways, though its precise role in TB pathogenesis remains largely un...

High-throughput Kinetics using capillary Electrophoresis and Robotics (HiKER) platform used to study T7, T3, and Sp6 RNA polymerase misincorporation.

T7 RNA Polymerase (RNAP) is a widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as key analysis tools for probing the nucleotide addition mechanisms of T7 RNAP and other polymerases. However, sequencing gels are low-throughput limiting their utility for comprehensive enzyme analysis. Here, we report the develo...

Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.

This genetic association study including 120 patients with type 2 diabetes mellitus (T2DM) and 166 non-diabetic individuals aimed to investigate the a...

Deep Learning Methods for De Novo Peptide Sequencing.

Protein tandem mass spectrometry data are most often interpreted by matching observed mass spectra to a protein database derived from the reference ge...

XGBoost as a reliable machine learning tool for predicting ancestry using autosomal STR profiles - Proof of method.

The aim of this study was to test the validity of a predictive model of ancestry affiliation based on Short Tandem Repeat (STR) profiles. Frequencies ...

Integrated multi-omics and machine learning reveal a gefitinib resistance signature for prognosis and treatment response in lung adenocarcinoma.

Gefitinib resistance (GR) presents a significant challenge in treating lung adenocarcinoma (LUAD), highlighting the need for alternative therapies. Th...

Translation as a Biosignature.

Life on Earth relies on mechanisms to store heritable information and translate this information into cellular machinery required for biological activ...

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bact...

Integrative analysis and knowledgebase construction of key candidate genes and pathways in age-related macular degeneration.

Age-related macular degeneration is a retinal disease that severely impacts vision in the older population. Its gene-related heterogeneity has not bee...

Identification of CCR7 and CBX6 as key biomarkers in abdominal aortic aneurysm: Insights from multi-omics data and machine learning analysis.

Abdominal aortic aneurysm (AAA) is a severe vascular condition, marked by the progressive dilation of the abdominal aorta, leading to rupture if untre...

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using an AI Chatbot as a Genetic Counselor: Clinical Study.

BACKGROUND: Hereditary breast and ovarian cancer (HBOC) is a major type of hereditary cancer. Establishing effective screening to identify high-risk i...

A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.

Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses l...

Identification of biomarkers for the diagnosis in colorectal polyps and metabolic dysfunction-associated steatohepatitis (MASH) by bioinformatics analysis and machine learning.

Colorectal polyps are precursors of colorectal cancer. Metabolic dysfunction associated steatohepatitis (MASH) is one of metabolic dysfunction associa...

GFPrint™: A machine learning tool for transforming genetic data into clinical insights.

The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully expl...

Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.

BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to th...

Arithmetic abilities of SNP systems with astrocytes producing calcium.

Are the membrane systems able of performing arithmetic operations? In the last dozen years, there were published several implementations of the arithm...

Machine Learning Integration with Single-Cell Transcriptome Sequencing Datasets Reveals the Impact of Tumor-Associated Neutrophils on the Immune Microenvironment and Immunotherapy Outcomes in Gastric Cancer.

The characteristics of neutrophils play a crucial role in defining the tumor inflammatory environment. However, the function of tumor-associated neutr...

Insights to aging prediction with AI based epigenetic clocks.

Over the past century, human lifespan has increased remarkably, yet the inevitability of aging persists. The disparity between biological age, which r...

Graph Convolutional Network for AD and MCI Diagnosis Utilizing Peripheral DNA Methylation: Réseau de neurones en graphes pour le diagnostic de la MA et du TCL à l'aide de la méthylation de l'ADN périphérique.

OBJECTIVE: Blood DNA methylation (DNAm) alterations have been widely reported in the onset and progression of mild cognitive impairment (MCI) and Alzh...

A machine learning-based analysis of nationwide cancer comprehensive genomic profiling data across cancer types to identify features associated with recommendation of genome-matched therapy.

BACKGROUND: The low probability of identifying druggable mutations through comprehensive genomic profiling (CGP) and its financial and time costs hind...