Vidanagamachchi, Sugandima and Niranjan, Mahesan (2018) OPBI: an open pipeline for biomarker identification. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017. vol. 2017-December, IEEE Computer Society. pp. 1510-1514 . (doi:10.1109/IEEM.2017.8290145).
Abstract
Biomarker discovery is one particular pipeline utilized in shotgun proteomics, which is made up of series of phases starting from a set of mass spectrum files and ending with some significantly expressed proteins that are related to a particular disease condition. Different techniques and tools have been introduced to perform protein identification and biomarker identification, and they still consume days/hours to carry out the processes. Further, they ignore MS1 information and consider only the information included in MS2 spectra. In this paper, we present an open-source, R-based, accurate biomarker identification pipeline, which provides solutions to time consumption problem in current biomarker discovery pipelines and utilizes the information of MS1 spectra. The developed pipeline was validated using three raw datasets of PRIDE database. We observed around 2-4 times speed-up and FDR ranges from 0.0003 to 0.0009. The biomarker identification system is accurate and operates in a considerable speed than commonly used, open-source MaxQuant tool.
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- Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg) > Vision, Learning and Control (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Vision, Learning and Control (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Vision, Learning and Control (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Vision, Learning and Control > Vision, Learning and Control (pre 2018 reorg)
School of Electronics and Computer Science > Vision, Learning and Control > Vision, Learning and Control (pre 2018 reorg) - Faculties (pre 2018 reorg) > Faculty of Natural and Environmental Sciences (pre 2018 reorg) > Institute for Life Sciences (pre 2018 reorg)
Current Faculties > Faculty of Environmental and Life Sciences > Institute for Life Sciences > Institute for Life Sciences (pre 2018 reorg)
Institute for Life Sciences > Institute for Life Sciences (pre 2018 reorg)
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