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Reactome (http://www.reactome.org/) is a free, open-source, curated and peer-reviewed pathway database which provides multiple bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge.
Data analyses based on multiple bioinformatics tools produced a large body of biologically meaningful information, and revealed a number of genes such as SAMHD1, G6PD, GPD2 and ENO1, which have been reported to be related to immune response, blood biology, bone remodeling, and cancer respectively.
In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs.
It was also concluded that the most accurate sequence for genome comparison purposes results from hybrid 454-Illumina sequencing coupled with the use of multiple bioinformatics tools for identifying differences between genome sequences from closely related strains.
Genome annotation, genomic comparison and phylogenetic analyses were performed with the use of multiple bioinformatics tools like: BLAST+ 2.2.24, Glimmer3.0, RAST server, Geneious 4.8.5, ClustalW2 and MEGA5.
This is an informative article, describing how a specific tool (Cytoscape) has been integrated into an innovative framework (GenomeSpace) that enables seamless access to multiple bioinformatics tools.
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Genome annotation, multiple allingment to others baculoviruses and phylogegentic analises were perform with the use of multiple bioinformatic tools like: Glimmer3, HMMER web server, Geneious 7 and MEGA6.
We here propose to use an immunomic methodology combining genomic data and multiple bioinformatic tools to study the anti-viral CTL response.
We here use a combination of multiple bioinformatic tools and large amount of genomic data to compute the epitope repertoire presented by over 1300 viruses in many HLA alleles.
Starting with the E. coli CydX sequence known to produce a functional protein, a survey for homologues was conducted using multiple homology-based bioinformatics tools.
Assays are currently being developed for other diseases such as cancer [ 14, 15], combining the strengths of proteomics with powerful bioinformatics tools, utilising multiple protein biomarkers in data driven predictive assays.
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numerous bioinformatics tools
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various bioinformatics tools
multiple bioinformatics technologies
multiple bioinformatics programs
multiple bioinformatics methods
multiple bioinformatics approaches
multiple bioinformatics infrastructures
multiple bioinformatics algorithms
multiple admissions tools
multiple bioinformatics analyses
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