BioBam Supported Project – with OmicsBox. Researchers: Richard Lathe – Division of Infection Medicine, University of Edinburgh Medical School, Edinburgh, UK Project: In managing the COVID-19 pandemic there is an urgent need to understand why some people develop severe infection leading to hospitalization and mortality, whereas others are relatively unaffected.
If you reached the maximum number of computers linked to your subscription, this option allows you to unlink all the computers linked to your subscription and to activate new computers. Please note, only the person associated to the subscription can unlink the computers via the BioBam Account. If you logged in to your account and can not see your subscription
BioBam Supported Project – with OmicsBox. Researchers: Pr. Sami Aifa from the Laboratory of Molecular and Cellular Screening Processes (LPCMC) from the Centre of Biotechnology of Sfax, Tunisia Dr. Amor Mosbah from the Laboratory of Biotechnology and Valorization of Bio-Geo-Ressources (LBVBGR) from the Superior Institute of Biotechnology of Sidi Thabet, Tunisia Dr. Salma Abdeljalil and Pr. Ali Gargouri from the
BioBam Supported Project – with OmicsBox. Researchers: Luis Fernando Saraiva Macedo Timmers – Coordinator – Univates, Brazil Rafael Andrade Caceres – UFCSPA, Brazil Leandro de Mattos Pereira, UFRJ, Brazil Fernando Ruggiero Bachega – UFCSPA, Brazil Marcia Ines Goettert – Univates, Brazil Luiz Augusto Basso – PUCRS, Brazil Project: Currently, a large amount of data is available regarding the new SARS-CoV-2
BioBam Scholarship Supported Project – with OmicsBox. Researchers: Mr. Arun Arumugaperumal Mr. Sayan Paul and Miss Saranya Lathakumari, PhD students Dr. Sudhakar Sivasubramaniam Abstract The earthworm Eisenia fetida has a symbiotic bacteria named Verminephrobacter eiseniae in its nephridia. A new strain of V. eiseniae msu was found out and the genome of the bacteria was found hidden in the genome
De novo transcriptome assemblies are required to analyze RNA-seq data from a species for which there is no reference genome. Once the assembly is complete, researchers need to know how good it is or compare the quality of similar assemblies generated by different parameters. There are several ways to characterize the quality of transcriptome assemblies. A good metric of assembly
Most transcripts assembled from eukaryotic and prokaryotic RNA-Seq data are expected to code for proteins. The most practical procedure to identify likely coding transcripts is a sequence homology search, such as by BLASTX, against sequences from a well-annotated and related species. Predicting coding regions is crucial to determine the molecular role that transcripts play in the cell. Unfortunately, such well-annotated
DNA sequencing is the process of determining the nucleic acid sequence in DNA, and it is the technology by which the genome of a species can be characterized. Despite the advent of next-generation sequencing, current DNA sequencing technologies cannot read whole genomes at once, but rather reads small pieces of between 20 and 30.000 bases, depending on the technology used.
It is possible to run Blast only on the differential expressed genes and not on all the data with OmicsBox. One has to select only those sequences that have differential expressed genes in the OmicsBox project.First, make sure that the name of the sequences in the project match the ones from the differential expression results.
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