TY  - 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 . .