DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases
Authors
Bajić, Vladan
Salhi, Adil
Lakota, Katja
Radovanović, Aleksandar
Razali, Rozaimi
Živković, Lada

Spremo-Potparević, Biljana

Uludag, Mahmut
Tifratene, Faroug
Motwalli, Olaa
Marchand, Benoit
Bajić, Vladimir
Gojobori, Takashi
Isenović, Esma
Essack, Magbubah
Article (Published version)
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More 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.
Source:
PLoS ONE, 2022, 17, 7Publisher:
- Public Library of Science
Funding / projects:
- The Laboratory of Radiobiology and Molecular Genetics
- Vinca Institute of Nuclear Sciences
- University of Belgrade, Belgrade, Serbia
- King Abdullah University of Science and Technology (KAUST),
- Computational Bioscience Research Center (CBRC)
- Thuwal, Saudi Arabia.
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PharmacyTY - JOUR AU - Bajić, Vladan AU - Salhi, Adil AU - Lakota, Katja AU - Radovanović, Aleksandar AU - Razali, Rozaimi AU - Živković, Lada AU - Spremo-Potparević, Biljana AU - Uludag, Mahmut AU - Tifratene, Faroug AU - Motwalli, Olaa AU - Marchand, Benoit AU - Bajić, Vladimir AU - Gojobori, Takashi AU - Isenović, Esma AU - Essack, Magbubah PY - 2022 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4249 AB - More 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. PB - Public Library of Science T2 - PLoS ONE T1 - DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases VL - 17 IS - 7 DO - 10.1371/journal.pone.0271737 ER -
@article{ author = "Bajić, Vladan and Salhi, Adil and Lakota, Katja and Radovanović, Aleksandar and Razali, Rozaimi and Živković, Lada and Spremo-Potparević, Biljana and Uludag, Mahmut and Tifratene, Faroug and Motwalli, Olaa and Marchand, Benoit and Bajić, Vladimir and Gojobori, Takashi and Isenović, Esma and Essack, Magbubah", year = "2022", abstract = "More 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.", publisher = "Public Library of Science", journal = "PLoS ONE", title = "DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases", volume = "17", number = "7", doi = "10.1371/journal.pone.0271737" }
Bajić, V., Salhi, A., Lakota, K., Radovanović, A., Razali, R., Živković, L., Spremo-Potparević, B., Uludag, M., Tifratene, F., Motwalli, O., Marchand, B., Bajić, V., Gojobori, T., Isenović, E.,& Essack, M.. (2022). DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases. in PLoS ONE Public Library of Science., 17(7). https://doi.org/10.1371/journal.pone.0271737
Bajić V, Salhi A, Lakota K, Radovanović A, Razali R, Živković L, Spremo-Potparević B, Uludag M, Tifratene F, Motwalli O, Marchand B, Bajić V, Gojobori T, Isenović E, Essack M. DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases. in PLoS ONE. 2022;17(7). doi:10.1371/journal.pone.0271737 .
Bajić, Vladan, Salhi, Adil, Lakota, Katja, Radovanović, Aleksandar, Razali, Rozaimi, Živković, Lada, Spremo-Potparević, Biljana, Uludag, Mahmut, Tifratene, Faroug, Motwalli, Olaa, Marchand, Benoit, Bajić, Vladimir, Gojobori, Takashi, Isenović, Esma, Essack, Magbubah, "DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases" in PLoS ONE, 17, no. 7 (2022), https://doi.org/10.1371/journal.pone.0271737 . .