The MPI Bioinformatics Toolkit for protein sequence analysis

By Andreas Biegert, Christian E. Mayer, Michael Remmert, Johannes Söding, Andrei N. Lupas. 2006

291 citations recorded by the source corpus.

The MPI Bioinformatics Toolkit is an interactive web service which offers access to a great variety of public and in-house bioinformatics tools. They are grouped into different sections that support sequence searches, multiple alignment, secondary and tertiary structure prediction and classification. Several public tools are offered in customized versions that extend their functionality. For example, PSI-BLAST can be run against regularly updated standard databases, customized user databases or selectable sets of genomes. Another tool, Quick2D, integrates the results of various secondary structure, transmembrane and disorder prediction programs into one view. The Toolkit provides a friendly and intuitive user interface with an online help facility. As a key feature, various tools are interconnected so that the results of one tool can be forwarded to other tools. One could run PSI-BLAST, parse out a multiple alignment of selected hits and send the results to a cluster analysis tool. The Toolkit framework and the tools developed in-house will be packaged and freely available under the GNU Lesser General Public Licence (LGPL). The Toolkit can be accessed at .

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Protein Sequence Analysis Using the MPI Bioinformatics Toolkit (2020, methodology): “…our work at the interface of computational and experimental biology, we launched the MPI Bioinformatics Toolkit in 2005 to provide researchers in the life sciences with easy, web-based access to the best-performing bioinformatics tools and databases (Biegert, Mayer, Remmert, Soding, & Lupas, 2006).”
The MPI bioinformatics Toolkit as an integrative platform for advanced protein sequence and structure analysis (2016, methodology): “This evolved into the MPI Bioinformatics Toolkit, which we made public in a beta version in 2005 with 30 tools and published in the 2006 Web Server issue of Nucleic Acids Research (4).”
Evolution of nutritional modes of Ceratobasidiaceae (Cantharellales, Basidiomycota) as revealed from publicly available ITS sequences (2013, methodology): “…topology and to reduce tree size for convenient display, the dataset was collapsed into 288 entries by clustering the sequences with BLASTclust (Biegert et al. 2006) based on 99 % sequence similarity and 90 % coverage criteria (99 % threshold was used instead of 97 %, to keep all anastomosis…”
Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains (2016, methodology): “A more complex alternative for the confirmatory steps (A2 and B6) is to create HMMs for the query and target regions with 8 iterations, and align them pairwise with HHalign.63 function requires the predicted PH-like domain to be intact.”