probeBase - an online resource for rRNA-targeted oligonucleotide probes and primers: new features 2016

Daniel Greuter
2017 unpublished
Modern technologies in molecular biology, such as next generation sequencing, allow researchers to perform more accurate and advanced analysis of organisms. Today, scientists can identify microorganisms via their unique genetic fingerprint. With the occurrence of these new methods, the number of sequenced microbial genomes has exploded over the last decades. To gather and preserve all available information regarding those sequences, online databases, like probeBase, have been established.
more » ... ase was created in 2002 by the Microbial Ecology Group staff at the Lehrstuhl für Mikrobiologie of the Technische Universität München. Over the years, the database grew and more people used it for their research. The popularity pushed it to its technical limits and made a reimplementation unavoidable. This thesis deals with the reimplementation and describes all the necessary concepts, processes and technical aspects which made the new probeBase possible. The new web resource uses Drupal, a popular open-source content management system, as its foundation. Such frameworks allow maintainers to manage web applications more efficiently. Additional features can be added via a web interface and the core functions can be extended with custom modules. All functionalities the new probeBase offers have been implemented in such extensions. The new probe matching feature is powered by VMATCH. This tool utilises enhanced suffix arrays to perform fast sequencing matching and allows up to two mismatches between probes and user-submitted sequences. Besides the reimplementation of the original toolset, new features and enhancements like the proxy matching have been added. This function identifies near full-length rRNA equivalent for short query sequences. Found sequences are then matched with all oligonucleotides available in the probeBase database to get possible probe candidates of the original user submission.
doi:10.25365/thesis.50026 fatcat:2ck6a574knekfprmxwg5t57hhy