Activate development on Blast2GO was discontinued in 2018. All its functionality and more new features are now part of OmicsBox. Because Blast2GO is no longer updated, some of its functions may have stopped working because web services have changed or security certificates have expired, among other things. It is highly recommended to use OmicsBox instead of Blast2GO to benefit from
This project reproduces the study carried out by Hittalmani S. et al. in 2016 about the S. oryzae fungus, which causes sheath rot of rice. We used OmicsBox for all necessary steps till functional analysis in order to predict pathogenic functions. (Original research paper: https://doi.org/10.1186/s12864-016-2599-0)
In this analysis, we will reproduce a study carried out by Michaela M. Martis et al. in 2017 with OmicsBox. (http://doi.org/10.1371/journal.pone.0185182) Introduction Ascaridia galli is an intestinal parasite that infects a wide range of domestic birds. It is especially important in European farms, where it parasites laying hens and causes economic problems. The only available treatments are the Benzimidazole derivatives,
Whole genome functional annotation of Solanum lycopersicum with OmicsBox functional annotation module.
This article explains how to export a GFF file with GO terms in Blast2GO.
This article explains how to start functional enrichment analysis of pairwise differential genes in Blast2GO.
This article explains how to create ID lists of either Blast results or differential expressed genes in Blast2GO.
When running GeneFinding the sequences receive a name with the predicted genes. The first part of the sequence identifier comes from the genome reference sequence name (de-novo assembly) and then a _orfx is appended, where x is a number. Sometimes this name is not useful to proceed with downstream analysis or compare results from other experiments. Is there any way
What is a Gene Venn Diagram? A Gene Venn Diagram is a graphical representation in the form of overlapping circles widely used to represent relationships among different genes (IDs). High-throughput sequencing technologies generate large amounts of data sets coming from multiomics studies. At the transcriptomic level, differential expression analysis appears to be a highly important field of study in bioinformatics
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