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DES-Amyloidoses "Amyloidoses through the looking-glass": A knowledgebase developed for exploring and linking information related to human amyloid-related diseases.
Bajic, Vladan P; Salhi, Adil; Lakota, Katja; Radovanovic, Aleksandar; Razali, Rozaimi; Zivkovic, Lada; Spremo-Potparevic, Biljana; Uludag, Mahmut; Tifratene, Faroug; Motwalli, Olaa; Marchand, Benoit; Bajic, Vladimir B; Gojobori, Takashi; Isenovic, Esma R; Essack, Magbubah.
Afiliación
  • Bajic VP; Institute of Nuclear Sciences "VINCA", Laboratory for Radiobiology and Molecular Genetics, University of Belgrade, Belgrade, Republic of Serbia.
  • Salhi A; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Lakota K; Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia.
  • Radovanovic A; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Razali R; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Zivkovic L; Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia.
  • Spremo-Potparevic B; Department of Pathobiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia.
  • Uludag M; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Tifratene F; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Motwalli O; Saudi Electronic University (SEU), College of Computing and Informatics, Madinah, Kingdom of Saudi Arabia.
  • Marchand B; New York University, Abu Dhabi, UAE.
  • Bajic VB; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Gojobori T; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Isenovic ER; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
  • Essack M; Institute of Nuclear Sciences "VINCA", Laboratory for Radiobiology and Molecular Genetics, University of Belgrade, Belgrade, Republic of Serbia.
PLoS One ; 17(7): e0271737, 2022.
Article en En | MEDLINE | ID: mdl-35877764
ABSTRACT
More 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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Asunto principal: Enfermedad de Alzheimer / Amiloidosis Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Asunto principal: Enfermedad de Alzheimer / Amiloidosis Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article