Center for Bioinformatics, Saarland University, Building E1.1, 66041 Saarbrücken, Germany.
Published: July 2007
AI Article Synopsis
Article Abstract
We present a comprehensive and efficient gene set analysis tool, called 'GeneTrail' that offers a rich functionality and is easy to use. Our web-based application facilitates the statistical evaluation of high-throughput genomic or proteomic data sets with respect to enrichment of functional categories. GeneTrail covers a wide variety of biological categories and pathways, among others KEGG, TRANSPATH, TRANSFAC, and GO. Our web server provides two common statistical approaches, 'Over-Representation Analysis' (ORA) comparing a reference set of genes to a test set, and 'Gene Set Enrichment Analysis' (GSEA) scoring sorted lists of genes. Besides other newly developed features, GeneTrail's statistics module includes a novel dynamic-programming algorithm that improves the P-value computation of GSEA methods considerably. GeneTrail is freely accessible at http://genetrail.bioinf.uni-sb.de.
The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary-and largely uncharacterized-genetics of adsorption, injection, cell take-over, and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions among 51 strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days.
Considerable differences in molecular characteristics have been defined between non-smoker and smokers in patients with lung adenocarcinoma (LUAD), yet studies on open chromatin patterns associated with LUAD progression caused by smoking are still lacking. Here, we constructed a novel network based on correlations between each ATAC-seq peak from TCGA data using our previously developed algorithm. Subsequently, principal component analysis was performed on LUAD samples with retained peaks filtered by the correlation network, and pathway analysis was conducted to identify potential pathways involved.
Unresectable stage III NSCLC is now treated with chemoradiation (CRT) followed by immune checkpoint inhibitors (ICI). Pneumonitis, a common CRT complication, has heightened risk with ICI, potentially causing severe outcomes. Currently, there are no biomarkers to predict pneumonitis risk or differentiate between radiation-induced pneumonitis (RTP) and ICI-induced pneumonitis (IIP).
Fission yeast is the ideal model organism for studying telomere maintenance in higher eukaryotes. Telomere length has been directly correlated with life expectancy and the onset of aging-related diseases in mammals. In this study, we developed a novel simple, and reproducible method to measure the telomere length, by investigating the effect of Caffeine and Cisplatin on the telomere length in fission yeast.
Department of Pharmacology and Toxicology, University of Louisville, 505 S. Hancock Street, Louisville, KY 40202, USA; Center for Integrative Environmental Health Sciences, University of Louisville, 505 S. Hancock Street, Louisville, KY 40202, USA. Electronic address:
Dysregulated miRNA expression contributes to development of arsenic-induced cutaneous squamous cell carcinoma (cSCC). hsa-miR-186 (miR-186) is overexpressed in arsenical cSCC tissues as well as in preclinical cell line model of arsenical cSCC. Simultaneous miR-186 overexpression and chronic inorganic trivalent arsenite (iAs; 100 nM) exposure transformed human HaCaT cell line preferentially over miR-186 overexpression or iAs exposure alone.
