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1.
Bioinformatics ; 39(4)2023 04 03.
Artículo en Inglés | MEDLINE | ID: mdl-37018146

RESUMEN

SUMMARY: We developed the eccDB database to integrate available resources for extrachromosomal circular DNA (eccDNA) data. eccDB is a comprehensive repository for storing, browsing, searching, and analyzing eccDNAs from multispecies. The database provides regulatory and epigenetic information on eccDNAs, with a focus on analyzing intrachromosomal and interchromosomal interactions to predict their transcriptional regulatory functions. Moreover, eccDB identifies eccDNAs from unknown DNA sequences and analyzes the functional and evolutionary relationships of eccDNAs among different species. Overall, eccDB offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher the molecular regulatory mechanisms of eccDNAs. AVAILABILITY AND IMPLEMENTATION: eccDB is freely available at http://www.xiejjlab.bio/eccDB.


Asunto(s)
Cromatina , ADN Circular , Cromatina/genética , Cromosomas , ADN , Secuencia de Bases
2.
Front Genet ; 13: 839589, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35432441

RESUMEN

Esophageal squamous cell carcinoma (ESCC) is a common malignant gastrointestinal tumor threatening global human health. For patients diagnosed with ESCC, determining the prognosis is a huge challenge. Due to their important role in tumor progression, long non-coding RNAs (lncRNAs) may be putative molecular candidates in the survival prediction of ESCC patients. Here, we obtained three datasets of ESCC lncRNA expression profiles (GSE53624, GSE53622, and GSE53625) from the Gene Expression Omnibus (GEO) database. The method of statistics and machine learning including survival analysis and LASSO regression analysis were applied. We identified a six-lncRNA signature composed of AL445524.1, AC109439.2, LINC01273, AC015922.3, LINC00547, and PSPC1-AS2. Kaplan-Meier and Cox analyses were conducted, and the prognostic ability and predictive independence of the lncRNA signature were found in three ESCC datasets. In the entire set, time-dependent ROC curve analysis showed that the prediction accuracy of the lncRNA signature was remarkably greater than that of TNM stage. ROC and stratified analysis indicated that the combination of six-lncRNA signature with the TNM stage has the highest accuracy in subgrouping ESCC patients. Furthermore, experiments subsequently confirmed that one of the lncRNAs LINC01273 may play an oncogenic role in ESCC. This study suggested the six-lncRNA signature could be a valuable survival predictor for patients with ESCC and have potential to be an auxiliary biomarker of TNM stage to subdivide ESCC patients more accurately, which has important clinical significance.

3.
Database (Oxford) ; 20222020 Jan 17.
Artículo en Inglés | MEDLINE | ID: mdl-35134148

RESUMEN

Accessible chromatin refers to the active regions of a chromosome that are bound by many transcription factors (TFs). Changes in chromatin accessibility play a critical role in tumorigenesis. With the emergence of novel methods like Assay for Transposase-accessible Chromatin Sequencing, a sequencing method that maps chromatin-accessible regions (CARs) and enables the computational analysis of TF binding at chromatin-accessible sites, the regulatory landscape in cancer can be dissected. Herein, we developed a comprehensive cancer chromatin accessibility database named CATA, which aims to provide available resources of cancer CARs and to annotate their potential roles in the regulation of genes in a cancer type-specific manner. In this version, CATA stores 2 991 163 CARs from 23 cancer types, binding information of 1398 TFs within the CARs, and provides multiple annotations about these regions, including common single nucleotide polymorphisms (SNPs), risk SNPs, copy number variation, somatic mutations, motif changes, expression quantitative trait loci, methylation and CRISPR/Cas9 target loci. Moreover, CATA supports cancer survival analysis of the CAR-associated genes and provides detailed clinical information of the tumor samples. Database URL: CATA is available at http://www.xiejjlab.bio/cata/.

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