BiBi Microbial Bioinformatics provides bioinformatics support, compute resources and software tools for the field of microbial genome research. In the frame of de.NBI the center constitutes a part of the BiGi Bioinformatics Resource Center combining bioinformatics expertise and facilities at Bielefeld University and Gießen Justus-Liebig University. In 2016, the microbial genome analysis portfolio was complemented for metaproteome data analysis with the new partner Magdeburg Otto-von-Guericke-University.
BiBi Microbial Bioinformatics operates, maintains and supports a wide range of software tools and applications providing solutions for microbial analytics, in particular, for metagenomics and postgenomics data analysis, data integration and data visualization. Here, emphasis is being placed on first-level user support and the provision of high-performance computing services for different user profiles.
Our portfolio of solutions for microbial bioinformatics ranges from pre-defined analysis workflows for common data analyses to comprehensive application software. This includes, for instance, EMGB for assembly-based metagenomics and Fusion for postgenomics data integration and combined analysis.
The Elastic MetaGenome Browser (EMGB) is a cloud-based metagenomic analysis pipeline, providing assembly of quality-controlled reads, binning of contigs, and taxonomic and functional annotation of consecutive gene predictions. EMGB, in particular, features a web interface to browse resulting metagenomic data in a very fast and effective manner. Up to now thousands of metagenome data sets have been analyzed in the de.NBI Cloud and are made available through the EMGB web interface.
Omics Fusion is a web application for the integrative analysis of omics data providing a comprehensive collection of new and established tools and visualization methods to support researchers in exploring multi-level omics data. The software focuses on data-rich high-throughput experiments from transcriptomics, proteomics and/or metabolomics, and offers convenient functionality for a) omics data manipulation, b) omics data analysis including variance analysis, regression and cluster analysis, and c) extensive data visualization. This includes, for example, methods to visualize combined omics data on metabolic pathway maps.