Browsing by Author "Siper, Metin Can"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
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 DORMAN: Database of reconstructed MetAbolic networks(IEEE, 2021) Özden, Furkan; Siper, Metin Can; Acarsoy, Necmi; Elmas, TuğrulcanGenome-scale reconstructed metabolic networks have provided an organism specific understanding of cellular processes and their relations to phenotype. As they are deemed essential to study metabolism, the number of organisms with reconstructed metabolic networks continues to increase. This everlasting research interest lead to the development of online systems/repositories that store existing reconstructions and enable new model generation, integration, and constraint-based analyses. While features that support model reconstruction are widely available, current systems lack the means to help users who are interested in analyzing the topology of the reconstructed networks. Here, we present the Database of Reconstructed Metabolic Networks - DORMAN. DORMAN is a centralized online database that stores SBML-based reconstructed metabolic networks published in the literature, and provides web-based computational tools for visualizing and analyzing the model topology. Novel features of DORMAN are (i) interactive visualization interface that allows rendering of the complete network as well as editing and exporting the model, (ii) hierarchical navigation that provides efficient access to connected entities in the model, (iii) built-in query interface that allow posing topological queries, and finally, and (iv) model comparison tool that enables comparing models with different nomenclatures, using approximate string matching. DORMAN is online and freely accessible at http://ciceklab.cs.bilkent.edu.tr/dorman.Item Open Access Efficient methods and readily customizable libraries for managing complexity of large networks(Public Library of Science, 2018) Doğrusöz, Uğur; Karaçelik, Alper; Safarli, İlkin; Balcı, Hasan; Dervishi, Leonard; Siper, Metin CanBackground One common problem in visualizing real-life networks, including biological pathways, is the large size of these networks. Often times, users find themselves facing slow, non-scaling operations due to network size, if not a “hairball” network, hindering effective analysis. One extremely useful method for reducing complexity of large networks is the use of hierarchical clustering and nesting, and applying expand-collapse operations on demand during analysis. Another such method is hiding currently unnecessary details, to later gradually reveal on demand. Major challenges when applying complexity reduction operations on large networks include efficiency and maintaining the user’s mental map of the drawing. Results We developed specialized incremental layout methods for preserving a user’s mental map while managing complexity of large networks through expand-collapse and hide-show operations. We also developed open-source JavaScript libraries as plug-ins to the web based graph visualization library named Cytsocape.js to implement these methods as complexity management operations. Through efficient specialized algorithms provided by these extensions, one can collapse or hide desired parts of a network, yielding potentially much smaller networks, making them more suitable for interactive visual analysis. Conclusion This work fills an important gap by making efficient implementations of some already known complexity management techniques freely available to tool developers through a couple of open source, customizable software libraries, and by introducing some heuristics which can be applied upon such complexity management techniques to ensure preserving mental map of users.Item Open Access Libraries and tools for viewing and editing biological maps in SBGN(2017-07) Siper, Metin CanInformation about cellular processes and pathways is becoming increasingly available in detailed, computable standard formats including Systems Biology Graphical Notation (SBGN). E ective visualization of this information is a key recurring requirement for biological data analysis, especially for -omic data. Biological data analysis is rapidly migrating to web based platforms; thus there is a substantial need for sophisticated web based pathway viewing and editing tools that support these platforms and other use cases. We propose to develop a modular software architecture to meet this need. This proposed architecture includes reusable web based libraries and easily customizable and embeddable tools developed using these libraries. Our libraries include SBGNViz.js, a Cytoscape.js based library providing a renderer and an API to develop tools visualizing pathway models represented by SBGN Diagrams, and ChiSE.js, an SBGNViz.js based library to visualize and construct pathway models represented in SBGN Diagrams, and miscellaneous Cytoscape.js extensions. Our tools are built using these libraries and include SBGNViz Viewer and Newt, which are sample applications for SBGNViz.js and ChiSE.js, respectively. Newt is being developed to become a rst web based, open source SBGN editor with full support for compound structures such as molecular complexes and compartment, advanced diagramming facilities including grid and alignment guidelines, static and incremental layout, and complexity management of large maps.Item Open Access Newt: a comprehensive web-based tool for viewing, constructing and analyzing biological maps(Oxford University Press, 2021-05-15) Balcı, Hasan; Siper, Metin Can; Saleh, Nasim; Safarli, İlkin; Roy, L.; Kılıçarslan, Merve; Özaydın, Rümeysa; Mazein, A.; Auffray, C.; Babur, Ö.; Demir, E.; Doğrusöz, UğurMotivation Visualization of cellular processes and pathways is a key recurring requirement for effective biological data analysis. There is a considerable need for sophisticated web-based pathway viewers and editors operating with widely accepted standard formats, using the latest visualization techniques and libraries. Results We developed a web-based tool named Newt for viewing, constructing and analyzing biological maps in standard formats such as SBGN, SBML and SIF. Availability and implementation Newt’s source code is publicly available on GitHub and freely distributed under the GNU LGPL. Ample documentation on Newt can be found on http://newteditor.org and on YouTube.