Anthropoides virgo
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA194294 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Warramaba virgo breed:WA Genome sequencing
| PRJNA1288686 | ENA
Project description:Conus virgo isolate:MNHN-IM-2013-54919 Raw sequence reads
| PRJNA992222 | ENA
Project description:Mass Spectrometric Characterisation of contryphans.
2023-02-01 | PXD035431 | Pride
Project description:BackgroundRNA Editing is a type of post-transcriptional modification that takes place in the eukaryotes. It alters the sequence of primary RNA transcripts by deleting, inserting or modifying residues. Several forms of RNA editing have been discovered including A-to-I, C-to-U, U-to-C and G-to-A. In recent years, the application of global approaches to the study of A-to-I editing, including high throughput sequencing, has led to important advances. However, in spite of enormous efforts, the real biological mechanism underlying this phenomenon remains unknown.DescriptionIn this work, we present VIRGO (http://atlas.dmi.unict.it/virgo/), a web-based tool that maps Ato-G mismatches between genomic and EST sequences as candidate A-to-I editing sites. VIRGO is built on top of a knowledge-base integrating information of genes from UCSC, EST of NCBI, SNPs, DARNED, and Next Generations Sequencing data. The tool is equipped with a user-friendly interface allowing users to analyze genomic sequences in order to identify candidate A-to-I editing sites.ConclusionsVIRGO is a powerful tool allowing a systematic identification of putative A-to-I editing sites in genomic sequences. The integration of NGS data allows the computation of p-values and adjusted p-values to measure the mapped editing sites confidence. The whole knowledge base is available for download and will be continuously updated as new NGS data becomes available.
| S-EPMC3837470 | biostudies-literature
Project description:Center for Common Disease Genomics [CCDG] – Cardiovascular: VIRGO: Variation in Recovery - Role of Gender on Outcomes of Young Acute Myocardial Infarction (AMI) Patients
| PRJNA357932 | ENA
Project description:Various space missions have measured the total solar irradiance (TSI) since 1978. Among them the experiments Precision Monitoring of Solar Variability (PREMOS) on the PICARD satellite (2010-2014) and the Variability of Irradiance and Gravity Oscillations (VIRGO) on the mission Solar and Heliospheric Observatory, which started in 1996 and is still operational. Like most TSI experiments, they employ a dual-channel approach with different exposure rates to track and correct the inevitable degradation of their radiometers. Until now, the process of degradation correction has been mostly a manual process based on assumed knowledge of the sensor hardware. Here we present a new data-driven process to assess and correct instrument degradation using a machine-learning and data fusion algorithm, that does not require deep knowledge of the sensor hardware. We apply the algorithm to the TSI records of PREMOS and VIRGO and compare the results to the previously published results. The data fusion part of the algorithm can also be used to combine data from different instruments and missions into a composite time series. Based on the fusion of the degradation-corrected VIRGO/PMO6 and VIRGO/DIARAD time series, we find no significant change (i.e [Formula: see text] W/m[Formula: see text]) between the TSI levels during the two most recent solar minima in 2008/09 and 2019/20. The new algorithm can be applied to any TSI experiment that employs a multi-channel philosophy for degradation tracking. It does not require deep technical knowledge of the individual radiometers.
| S-EPMC8035225 | biostudies-literature