DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases
AuthorsBajic, Vladan P.
Bajic, Vladimir B.
Isenovic, Esma R.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Research Planning and Partnership
Applied Mathematics and Computational Science Program
Biological and Environmental Science and Engineering (BESE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/679877
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AbstractMore than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer’s disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities’ influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.
CitationBajic, V. P., Salhi, A., Lakota, K., Radovanovic, A., Razali, R., Zivkovic, L., Spremo-Potparevic, B., Uludag, M., Tifratene, F., Motwalli, O., Marchand, B., Bajic, V. B., Gojobori, T., Isenovic, E. R., & Essack, M. (2022). DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases. PLOS ONE, 17(7), e0271737. https://doi.org/10.1371/journal.pone.0271737
SponsorsThis work is part of the collaboration between the Laboratory of Radiobiology and Molecular Genetics, Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia and King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia. This work has been supported by the Ministry of Education, Science and Technological Development, Republic of Serbia, and by the KAUST grant OSR#4129 (to EI and VBB), which also supported SZ and VPB. VBB has been supported by the KAUST Base Research Fund (BAS/1/1606-01-01), while ME has been supported by KAUST Office of Sponsored Research (OSR) grant no. FCC/1/1976-20-01. TG has been supported by the King Abdullah University of Science and Technology (KAUST) Base Research Fund (BAS/1/1059-01-01).
PublisherPublic Library of Science (PLoS)
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