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RNA-Seq [1] [2] [3] is a technique [4] that allows transcriptome studies (see also Transcriptomics technologies) based on next-generation sequencing technologies. This technique is largely dependent on bioinformatics tools developed to support the different steps of the process.
Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription .
Galaxy was originally written for biological data analysis, particularly genomics. The set of available tools has been greatly expanded over the years and Galaxy is now also used for gene expression, genome assembly, proteomics, epigenomics, transcriptomics and host of other disciplines in the life
Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, [1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays).
Single-cell RNA sequencing (scRNA-seq) is a recently developed technique that allows the analysis of the transcriptome of single cells, including bacteria. [25] With single-cell transcriptomics, subpopulations of cell types that constitute the tissue of interest are also taken into consideration. [26]
It is a research tool often employed in functional genomics research on non-model species. [11] It works by blasting assembled contigs against a non-redundant protein database (at NCBI), then annotating them based on sequence similarity. GOanna is another GO annotation program specific for animal and agricultural plant gene products that works ...
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GenMAPP was developed by biologists and is focused on pathway visualization for bench biologists. Unlike many other computational systems biology tools, GenMAPP is not designed for cell/systems modeling; it focuses on the immediate needs of bench biologists by enabling them to rapidly interpret genomic data with an intuitive, easy-to-use interface.