Browsing by Subject "Biocuration"
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Item Open Access Collaborative workspaces for pathway curation(CEUR-WS, 2016-08) Durupınar-Babur, F.; Siper, Metin Can; Doğrusöz, Uğur; Bahceci, İstemi; Babur, O.; Demir, E.We present a web based visual biocuration workspace, focusing on curating detailed mechanistic pathways. It was designed as a flexible platform where multiple humans, NLP and AI agents can collaborate in real-time on a common model using an event driven API. We will use this platform for exploring disruptive technologies that can scale up biocuration such as NLP, human-computer collaboration, crowd-sourcing, alternative publishing and gamification. As a first step, we are designing a pilot to include an author-curation step into the scientific publishing, where the authors of an article create formal pathway fragments representing their discovery- heavily assisted by computer agents. We envision that this "microcuration" use-case will create an excellent opportunity to integrate multiple NLP approaches and semi-automated curation. © 2016, CEUR-WS. All rights reserved.Item Open Access Community-driven roadmap for integrated disease maps(Oxford University Press, 2018) Ostaszewski, M.; Gebel, S.; Kuperstein, I.; Mazein, A.; Zinovyev, A.; Doğrusöz, Uğur; Hasenauer, J.; Fleming, R. M. T.; Novere, N. L.; Gawron, P.; Ligon, T.; Niarakis, A.; Nickerson, D.; Weindl, D.; Balling, R.; Barillot, E.; Auffray, C.; Schneider, R.The Disease Maps Project builds on a network of scientific and clinical groups that exchange best practices, share information and develop systems biomedicine tools. The project aims for an integrated, highly curated and user-friendly platform for disease-related knowledge. The primary focus of disease maps is on interconnected signaling, metabolic and gene regulatory network pathways represented in standard formats. The involvement of domain experts ensures that the key disease hallmarks are covered and relevant, up-to-date knowledge is adequately represented. Expert-curated and computer readable, disease maps may serve as a compendium of knowledge, allow for data-supported hypothesis generation or serve as a scaffold for the generation of predictive mathematical models. This article summarizes the 2nd Disease Maps Community meeting, highlighting its important topics and outcomes. We outline milestones on the roadmap for the future development of disease maps, including creating and maintaining standardized disease maps; sharing parts of maps that encode common human disease mechanisms; providing technical solutions for complexity management of maps; and Web tools for in-depth exploration of such maps. A dedicated discussion was focused on mathematical modeling approaches, as one of the main goals of disease map development is the generation of mathematically interpretable representations to predict disease comorbidity or drug response and to suggest drug repositioning, altogether supporting clinical decisions.