Learn to use the GenMAPP resource, a freely available open source software application for visualizing microarray data in the context of biological pathways. Learning to use this application will provide the researcher with an easy to use tool for viewing expression data within a biological pathway. The example data set used in the exercises can be downloaded and saved here.
You will learn:
This tutorial is a part of the tutorial group Interaction resources. You might find the other tutorials in the group interesting:
Pathway Interaction Database: A resource of pathway and network data and displays
MINT: Molecular Interaction Database
Cytoscape: An open-source software platform used for visualization and analysis of molecular interaction and network data
BiologicalNetworks: Analyze and visualize molecular interaction networks
BioSystems: Database of Biological Systems
Reactome Legacy: Older version of the current Reactome knowledgebase of biological processes.
Reactome: Knowledgebase of biological processes
GeneMANIA: GeneMANIA: Fast Gene Function Predictions
VisANT: A web-based or downloadable software platform used for visualization and analysis of networks and interaction pathways
InterPro: A comprehensive protein signature resource
IntAct protein interaction database: IntAct is an open source database and analysis resource for protein interaction data
KEGG: KEGG, The Kyoto Encyclopedia of Genes and Genomes
Pathways and Interactions : Tools that are involved with protein interactions and pathway features. Some tools are primarily repositories and some offer analysis options.
Open source molecular modeling--finally?: My Bio SmartBrief newsletter today had a reference to a paper in a rather...um...obscure journal. Maybe it is just something I have missed over the years, but the Journal of the Royal Society Interface...
Recent BioMed Central research articles citing this resource
Zhu Daochen et al., Biodegradation of alkaline lignin by Bacillus ligniniphilus L1. Biotechnology for Biofuels (2017) doi:10.1186/s13068-017-0735-y
Cui Li et al., De novo transcriptome and expression profile analyses of the Asian corn borer ( Ostrinia furnacalis ) reveals relevant flubendiamide response genes Transcriptomic methods. BMC Genomics (2017) doi:10.1186/s12864-016-3431-6
Yang Yang et al., Missing value imputation for microRNA expression data by using a GO-based similarity measure. BMC Bioinformatics (2016) doi:10.1186/s12859-015-0853-0
Tang Donge et al., Integrated analysis of mRNA, microRNA and protein in systemic lupus erythematosus-specific induced pluripotent stem cells from urine Human and rodent genomics. BMC Genomics (2016) doi:10.1186/s12864-016-2809-9
Aoki-Kinoshita F Kiyoko et al., Implementation of linked data in the life sciences at BioHackathon 2011. Journal of Biomedical Semantics (2015) doi:10.1186/2041-1480-6-3