AIMC Topic: Databases, Genetic

Clear Filters Showing 21 to 30 of 747 articles

Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS.

Scientific reports
Acute respiratory distress syndrome (ARDS) is one of the most common and serious complications in the development of sepsis. Endoplasmic reticulum stress (ERS) plays an important role in the pathophysiologic process of sepsis-associated ARDS. The aim...

A review on multi-omics integration for aiding study design of large scale TCGA cancer datasets.

BMC genomics
BACKGROUND: Rapid advancements in high-throughput sequencing technologies allow for detailed and accurate measurement of omics features within their biological context. The integration of different omics types creates heterogeneous datasets, presenti...

Identification and experimental validation of mitochondrial and endoplasmic reticulum stress related gene in diabetic nephropathy.

Scientific reports
Diabetic nephropathy (DN) is a kidney disease. Mitochondrial and endoplasmic reticulum stress (ERS) significantly contribute to diabetic nephropathy (DN), although the precise mechanisms involved have not yet been fully understood. The objective of t...

In-depth bioinformatics analysis uncovers the crosstalk genes and immune interactions among diagnostic markers linked to natural killer cells in patients with cirrhosis and sepsis.

Clinical and experimental medicine
Patients with cirrhosis face an elevated risk of developing sepsis, leading to an escalating mortality rate. This study focuses on the link between natural killer (NK) cells, cirrhosis, and sepsis. Our goal is to identify NK cell-related genes that c...

Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation.

BMC pharmacology & toxicology
BACKGROUND: Nonspecific orbital inflammation (NSOI), also known as idiopathic orbital inflammation, comprises a heterogeneous group of immune-mediated disorders affecting orbital tissues, unified by the absence of a defined etiology. Lactotransferrin...

varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction.

Genome medicine
BACKGROUND: Machine learning and artificial intelligence are increasingly being applied to identify phenotypically causal genetic variation. These data-driven methods require comprehensive training sets to deliver reliable results. However, large unb...

PuMA: PubMed gene/cell type-relation Atlas.

BMC bioinformatics
BACKGROUND: Rapid extraction and visualization of cell-specific gene expression is important for automatic cell type annotation, e.g. in single cell analysis. There is an emerging field in which tools such as curated databases or machine learning met...

Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells.

European journal of medical research
BACKGROUND: Cardioembolic stroke (CS) and atherosclerosis (AS) are closely related diseases. Ferroptosis, a novel form of programmed cell death, may play a key role in CS and AS. However, the pathophysiological mechanisms underlying their coexistence...

Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach.

Scientific reports
Acute myocardial infarction (AMI) is a serious heart disease with high fatality rates. The progress of AMI involves immune cell infiltration. However, suitable clinical diagnostic biomarkers and the roles of immune cells in AMI remain unknown. Three ...

Cross-attention graph neural networks for inferring gene regulatory networks with skewed degree distribution.

BMC bioinformatics
BACKGROUND: Inferring Gene Regulatory Networks (GRNs) from gene expression data is a pivotal challenge in systems biology. Most existing methods fail to consider the skewed degree distribution of genes, complicating the application of directed graph ...