hrvatski jezikClear Cookie - decide language by browser settings

msBiodat analysis tool, big data analysis for high-throughput experiments

Muñoz-Torres, Pau M.; Rokić, Filip; Belužić, Robert; Grbeša, Ivana; Vugrek, Oliver (2016) msBiodat analysis tool, big data analysis for high-throughput experiments. BioData Mining, 9 (26). ISSN 1756-0381

PDF - Published Version - article
Available under License Creative Commons Attribution.

Download (476kB) | Preview


Background Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of proteins. Filtering those data efficiently is the first step for extracting biologically relevant information. The filtering may increase interest by merging previous data with the data obtained from public databases, resulting in an accurate list of proteins which meet the predetermined conditions. Results In this article we present msBiodat Analysis Tool, a web-based application thought to approach proteomics to the big data analysis. With this tool, researchers can easily select the most relevant information from their MS experiments using an easy-to-use web interface. An interesting feature of msBiodat analysis tool is the possibility of selecting proteins by its annotation on Gene Ontology using its Gene Id, ensembl or UniProt codes. Conclusion The msBiodat analysis tool is a web-based application that allows researchers with any programming experience to deal with efficient database querying advantages. Its versatility and user-friendly interface makes easy to perform fast and accurate data screening by using complex queries. Once the analysis is finished, the result is delivered by e-mail. msBiodat analysis tool is freely available at

Item Type: Article
Uncontrolled Keywords: bioinformatics ; data analysis ; proteomics ; data mining ; mass spectrometry ; high-throughput analysis
Subjects: NATURAL SCIENCES > Biology
NATURAL SCIENCES > Interdisciplinary Natural Sciences
Divisions: Division of Molecular Medicine
Project titleProject leaderProject codeProject type
Enhancement of the Innovation Potential in SEE through new Molecular Solutions in Research and Development-INNOMOLUNSPECIFIED316289EK
Depositing User: Oliver Vugrek
Date Deposited: 05 Apr 2018 14:44
DOI: 10.1186/s13040-016-0104-6

Actions (login required)

View Item View Item


Downloads per month over past year

Increase Font
Decrease Font
Dyslexic Font