Prediction of Drug-Drug Interactions Using Pharmacological Similarities of Drugs

26th International Workshop on Database and Expert Systems Applications (DEXA) -- SEP 01-04, 2015 -- Valencia, SPAINWOS: 000380461300003Detection of potential Drug-Drug Interactions (DDIs) can reduce the costs associated drug administration and drug developments. It can also prevent serious adverse drug reactions possibly causing death. In this work, we have employed Rooted PageRank algorithm in DDI network with weights calculated using therapeutic, genomic, phenotypic and chemical similarity of drugs to discover unknown DDIs. Weighting approach is inspired from the method used in collaborative filtering to score for recommendation of an item to a user based on similarities of users or items. Different than our previous work, this method enables the integration of global structure of DDI network with similarity scores of interactions to predict new DDIs. We obtained significant performance enhancement both in terms of AUC and Precision on DDI networks extracted from Drugbank. Interestingly some weighting scheme increases AUC and decreases precision such as in case of applying chemical similarity weighting. However, weighting with drug genomic similarities decreases AUC and raises precision. Therapeutic and phenotypic similarity weighting has increased performance of both in AUC and precision

E.E.: Developing multi agent systems on semantic web environment using seagent platform

Abstract. In this paper, we discuss the development of a multi agent system working on the Semantic Web environment by using a new framework called SEAGENT. SEAGENT is a new agent development framework and platform, which includes built-in features for semantic web based multi agent system development. These features provide semantic supports such as a new specific content language for transferring semantic knowledge, specifically designed agent’s internal architecture to handle semantic knowledge, a new directory facilitator architecture based on semantic service matching engine and ontology management service to provide ontology translations within the platform’s ontologies. The implemented case study shows the effectiveness of these features in terms of semantically enriched multi agent system development.

Incidence and clinical characteristics of acute rheumatic fever in Turkey: Results of a nationwide multicentre study

© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)Aim: To evaluate the incidence and clinical features of acute rheumatic fever (ARF) in Turkey, following the revised Jones criteria in 2015. Methods: This multicentre study was designed by the Acquired Heart Diseases Working Group of the Turkish Pediatric Cardiology and Pediatric Cardiac Surgery Association in 2016. The data during the first attack of 1103 ARF patients were collected from the paediatric cardiologists between 1 January 2016 and 31 December 2016. Results: Turkey National Institute of Statistics records of 2016 were used for the determination of ARF incidence with regard to various cities and regions separately. The estimated incidence rate of ARF was 8.84/100 000 in Turkey. The ARF incidence varied considerably among different regions. The highest incidence was found in the Eastern Anatolia Region as 14.4/100 000, and the lowest incidence was found in the Black Sea Region as 3.3/100 000 (P < 0.05). Clinical carditis was the most common finding. The incidence of clinical carditis, subclinical carditis, polyarthritis, aseptic monoarthritis, polyarthralgia and Sydenham's Chorea was 53.5%, 29.1%, 52.8%, 10.3%, 18.6% and 7.9%, respectively. The incidences of clinical carditis, subclinical carditis, polyarthritis and polyarthralgia were found to be significantly different among different regions (P < 0.05). Conclusion: The findings of this nationwide screening of ARF suggest that Turkey should be included in the moderate-risk group