On the Impact of Granularity in Extracting Knowledge from Bioinformatics Data

Sean West, Hesham Ali

Abstract

With the rapidly increasing amount of various types of biological data currently available to researchers, the focus of the biomedical research community has been shifting from pure data generation towards the development of new methodologies for data analytics. Although many researchers continue to focus on approaches developed for analyzing single types of biological data, recent attempts have been made to utilize the availability of heterogeneous data sets that contain various types of data and try to establish tools for data integration and analysis in many bioinformatics applications. Such attempts are expected to increase significantly in this coming decade. While this can be viewed as a positive step towards advancing big data analytics in bioinformatics, it is critical that these integration methodologies are meticulously studied to ensure high quality of the knowledge extracted from the integrated data. In this work, we employ data integration methods to analyze biological data obtained from protein interaction networks and gene expression data. We conduct a study to show that potential problems can arise from integrating or fusing data obtained at different granularity levels and highlight the importance of developing advanced data fusing techniques to integrate various types of biological data for analytical purposes. Further, we explore the impact of granularity from a more formulized approach and the granularity levels significantly impact the quality of knowledge extracted from the integrated data.

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Paper Citation


in Harvard Style

West S. and Ali H. (2016). On the Impact of Granularity in Extracting Knowledge from Bioinformatics Data . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 92-103. DOI: 10.5220/0005778700920103


in Bibtex Style

@conference{bioinformatics16,
author={Sean West and Hesham Ali},
title={On the Impact of Granularity in Extracting Knowledge from Bioinformatics Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={92-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005778700920103},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - On the Impact of Granularity in Extracting Knowledge from Bioinformatics Data
SN - 978-989-758-170-0
AU - West S.
AU - Ali H.
PY - 2016
SP - 92
EP - 103
DO - 10.5220/0005778700920103