Genetics

Next-Generation Sequencing-Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods.

BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines for patients with advanced or metastatic disease.

Enhancing R-loop prediction with high-throughput sequencing data.

R-loops are three-stranded RNA and DNA hybrid structures that often occur in the genome and play important roles in a variety of cellular processes from bacteria to mammals. Sequencing methods profiling R-loops genome-wide have revealed that they can form co-transcriptionally at cell type specific genes and associate with specific chromatin states during cell differentiation and reprogramming. How...

DNA-based prediction of eye color in Latin American population applying Machine Learning models.

Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relat...

Gene as a Molecular Target Potentially Shared by Idiopathic Pulmonary Fibrosis and Pulmonary Hypertension: Drug Repurposing Prospect with Aminoglutethimide.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbid...

Linking autism risk genes to morphological and pharmaceutical screening by high-content imaging: Future directions and opinion.

Next-generation sequencing has identified risk genes with large effect sizes for autism spectrum disorders (ASD). Although functional analysis of indi...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble into functional neural networks. Studies investigat...

Tailoring Corynebacterium glutamicum for Sustainable Biomanufacturing: From Traditional to Cutting-Edge Technologies.

As the workhorse of industrial amino acid production, Corynebacterium glutamicum is the focus of this review, which provides a comprehensive overview ...

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.

The increasing demand for population-wide genomic screening and the limited availability of genetic counseling resources have created a pressing need ...

Development and validation of an interpretable risk prediction model for the early classification of thalassemia.

Thalassemia is an inherited blood disorder. Current diagnostic methods mainly rely on sophisticated equipment and specifically trained technicians. Th...

OptimDase: An Algorithm for Predicting DNA Binding Sites with Combined Feature Encoding.

Identifying DNA binding sites remains a critical task in bioinformatics, with applications ranging from gene regulation studies to drug design. Althou...

Updates on inherited arrhythmia syndromes (Brugada syndrome, long QT syndrome, CPVT, ARVC).

The inherited arrhythmia (IA) syndromes are a group of rare and complex conditions that may predispose individuals to ventricular arrhythmias and sudd...

Machine Learning Prediction on Birefringence of Nonlinear Optical Crystals and Polymorphs with Different Birefringence Activities.

Nonlinear optical (NLO) crystal materials have been widely used in the scientific and industrial fields. Birefringence is an important property of the...

Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (...

Identification and validation of blood leukocyte DNA methylation biomarkers for early detection of colorectal neoplasm.

BACKGROUND: Identifying high-risk populations for colorectal cancer (CRC) is critical for precise screening. This study aimed to develop a novel risk ...

Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.

Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multiple immune and inflammatory factors. Macrophages p...

Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data.

The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advan...

Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct ...

scGANSL: Graph Attention Network with Subspace Learning for scRNA-seq Data Clustering.

Single-cell RNA sequencing (scRNA-seq) has become a crucial technology for analyzing cellular diversity at the single-cell level. Cell clustering is c...

MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing splicing, mRNA structure, translation efficiency, an...

Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer.

Breast cancer is the most common type of cancer in women, and while current treatments can cure the majority of early-stage primary BC cases, recurren...