Welcome to the DES-Amyloidoses, the only knowledgebase (KB) dedicated to human amyloid-related diseases derived primarily through literature text-mining. 

Amyloidoses are a group of disorders characterized by intra- and/or extra-cellular amyloid deposits. More than 30 types of amyloids are linked to close to 50 diseases in humans. Alzheimers is one such disease with local amyloidosis of the brain. Another amyloidosis may have a more systematic character, such as AA amyloidosis, that may be a consequence of chronic inflammation. Since amyloidosis is complex pathologies, it will be highly beneficial to explore potential interactions of different biological entities in these pathologies. Still, there is currently no support system developed specifically to handle this complex and demanding task. 

To explore links between different components related to amyloidosis and human diseases, we processed published information in abstracts (PubMed) and full-text (PubMed Central) articles from 31,821 topic-relevant documents. Based on such information, we developed DES-Amyloidoses, an online knowledgebase that provides researchers with a platform from which they could more efficiently explore such information. The system utilizes concepts/terms from 19 curated thematic dictionaries mapped to the documents for analyses. 

DES-Amyloidosis allows exploring:

  1. individual statistically enriched concepts,
  2. individual pairs of concepts,
  3. co-occurrence of all concepts with an individual concept,
  4. interactive heterogeneous networks of associated concepts,
  5. hypotheses generated through semantic similarity, and
  6. export of the user’s results.

DES-Amyloidoses presents to users statistically enriched single and associated concepts based on a default false discovery rate (FDR) below 0.05, where FRD is calculated based on Benjamini–Hochberg procedure for correction for multiplicity testing.