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dc.creatorBajić, Vladan
dc.creatorSalhi, Adil
dc.creatorLakota, Katja
dc.creatorRadovanović, Aleksandar
dc.creatorRazali, Rozaimi
dc.creatorŽivković, Lada
dc.creatorSpremo-Potparević, Biljana
dc.creatorUludag, Mahmut
dc.creatorTifratene, Faroug
dc.creatorMotwalli, Olaa
dc.creatorMarchand, Benoit
dc.creatorBajić, Vladimir
dc.creatorGojobori, Takashi
dc.creatorIsenović, Esma
dc.creatorEssack, Magbubah
dc.date.accessioned2022-08-16T11:47:49Z
dc.date.available2022-08-16T11:47:49Z
dc.date.issued2022
dc.identifier.issn1932-6203
dc.identifier.urihttps://farfar.pharmacy.bg.ac.rs/handle/123456789/4249
dc.description.abstractMore than 30 types of amyloids are linked to close to 50 diseases in humans, the most prom- inent 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 net- work 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 rele- vant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data min- ing 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 infor- mation 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.
dc.publisherPublic Library of Science
dc.relationThe Laboratory of Radiobiology and Molecular Genetics
dc.relationVinca Institute of Nuclear Sciences
dc.relationUniversity of Belgrade, Belgrade, Serbia
dc.relationKing Abdullah University of Science and Technology (KAUST),
dc.relationComputational Bioscience Research Center (CBRC)
dc.relationThuwal, Saudi Arabia.
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourcePLoS ONE
dc.titleDES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases
dc.typearticle
dc.rights.licenseBY
dc.citation.volume17
dc.citation.issue7
dc.citation.rankM22
dc.identifier.doi10.1371/journal.pone.0271737
dc.identifier.scopus2-s2.0-85135282245
dc.identifier.fulltexthttp://farfar.pharmacy.bg.ac.rs/bitstream/id/10261/DES-Amyloidoses_Amyloidoses_through_pub_2022.pdf
dc.type.versionpublishedVersion


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