Browsing by Author "Demir, E."

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Open Access
Analyzing causal relationships in proteomic profiles using CausalPath
(Cell Press, 2021-12-17) Luna, A.; Siper, M. C.; Korkut, A.; Durupinar, F.; Aslan, J. E.; Sander, C.; Demir, E.; Babur, O.; Doğrusöz, Uğur
CausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset.
Open Access
Causal interactions from proteomic profiles: Molecular data meet pathway knowledge
(Cell Press, 2021-06) Babur, Ö.; Luna, A.; Korkut, A.; Durupınar, F.; Siper, M. C.; Doğrusöz, Uğur; Jacome, A. S. V.; Peckner, R.; Christiansen, K. E.; Jaffe, J.D; Spellman, P.T.; Aslan, J. E.; Sander, C.; Demir, E.
We present a computational method to infer causal mechanisms in cell biology by analyzing changes in high-throughput proteomic profiles on the background of prior knowledge captured in biochemical reaction knowledge bases. The method mimics a biologist's traditional approach of explaining changes in data using prior knowledge but does this at the scale of hundreds of thousands of reactions. This is a specific example of how to automate scientific reasoning processes and illustrates the power of mapping from experimental data to prior knowledge via logic programming. The identified mechanisms can explain how experimental and physiological perturbations, propagating in a network of reactions, affect cellular responses and their phenotypic consequences. Causal pathway analysis is a powerful and flexible discovery tool for a wide range of cellular profiling data types and biological questions. The automated causation inference tool, as well as the source code, are freely available at http://causalpath.org.
Open Access
Clustering spatial networks for aggregate query processing: a hypergraph approach
(Elsevier Ltd, 2008-03) Demir, E.; Aykanat, Cevdet; Cambazoglu, B. B.
In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature. In this work, we show that the state-of-the-art clustering graph model is not able to correctly capture the disk access costs of aggregate network operations. Moreover, we propose a novel clustering hypergraph model that correctly captures the disk access costs of these operations. The proposed model aims to minimize the total number of disk page accesses in aggregate network operations. Based on this model, we further propose two adaptive recursive bipartitioning schemes to reduce the number of allocated disk pages while trying to minimize the number of disk page accesses. We evaluate our clustering hypergraph model and recursive bipartitioning schemes on a wide range of road network datasets. The results of the conducted experiments show that the proposed model is quite effective in reducing the number of disk accesses incurred by the network operations. © 2007 Elsevier B.V. All rights reserved.
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.
Open Access
Efficiency and effectiveness of query processing in cluster-based retrieval
(Elsevier, 2004) Can, F.; Altingövde I.S.; Demir, E.
Our research shows that for large databases, without considerable additional storage overhead, cluster-based retrieval (CBR) can compete with the time efficiency and effectiveness of the inverted index-based full search (FS). The proposed CBR method employs a storage structure that blends the cluster membership information into the inverted file posting lists. This approach significantly reduces the cost of similarity calculations for document ranking during query processing and improves efficiency. For example, in terms of in-memory computations, our new approach can reduce query processing time to 39% of FS. The experiments confirm that the approach is scalable and system performance improves with increasing database size. In the experiments, we use the cover coefficient-based clustering methodology (C3M), and the Financial Times database of TREC containing 210158 documents of size 564 MB defined by 229748 terms with total of 29545234 inverted index elements. This study provides CBR efficiency and effectiveness experiments using the largest corpus in an environment that employs no user interaction or user behavior assumption for clustering. © 2003 Elsevier Ltd. All rights reserved.
Open Access
Efficient successor retrieval operations for aggregate query processing on clustered road networks
(Elsevier Inc., 2010) Demir, E.; Aykanat, Cevdet
Get-Successors (GS) which retrieves all successors of a junction is a kernel operation used to facilitate aggregate computations in road network queries. Efficient implementation of the GS operation is crucial since the disk access cost of this operation constitutes a considerable portion of the total query processing cost. Firstly, we propose a new successor retrieval operation Get-Unevaluated-Successors (GUS), which retrieves only the unevaluated successors of a given junction. The GUS operation is an efficient implementation of the GS operation, where the candidate successors to be retrieved are pruned according to the properties and state of the algorithm. Secondly, we propose a hypergraph-based model for clustering successively retrieved junctions by the GUS operations to the same pages. The proposed model utilizes query logs to correctly capture the disk access cost of GUS operations. The proposed GUS operation and associated clustering model are evaluated for two different instances of GUS operations which typically arise in Dijkstra's single source shortest path algorithm and incremental network expansion framework. Our simulation results show that the proposed successor retrieval operation together with the proposed clustering hypergraph model is quite effective in reducing the number of disk accesses in query processing. © 2010 Published by Elsevier Inc.
Open Access
Incremental cluster-based retrieval using compressed cluster-skipping inverted files
(Association for Computing Machinery, 2008-06) Altingovde, I. S.; Demir, E.; Can, F.; Ulusoy, Özgür
We propose a unique cluster-based retrieval (CBR) strategy using a new cluster-skipping inverted file for improving query processing efficiency. The new inverted file incorporates cluster membership and centroid information along with the usual document information into a single structure. In our incremental-CBR strategy, during query evaluation, both best(-matching) clusters and the best(-matching) documents of such clusters are computed together with a single posting-list access per query term. As we switch from term to term, the best clusters are recomputed and can dynamically change. During query-document matching, only relevant portions of the posting lists corresponding to the best clusters are considered and the rest are skipped. The proposed approach is essentially tailored for environments where inverted files are compressed, and provides substantial efficiency improvement while yielding comparable, or sometimes better, effectiveness figures. Our experiments with various collections show that the incremental-CBR strategy using a compressed cluster-skipping inverted file significantly improves CPU time efficiency, regardless of query length. The new compressed inverted file imposes an acceptable storage overhead in comparison to a typical inverted file. We also show that our approach scales well with the collection size. © 2008 ACM.
Open Access
Integrating biological pathways and genomic profiles with ChiBE 2
(BioMed Central Ltd., 2014) Babur, O.; Dogrusoz, U.; Çakır, M.; Aksoy, B. A.; Schultz, N.; Sander, C.; Demir, E.
Background: Dynamic visual exploration of detailed pathway information can help researchers digest and interpret complex mechanisms and genomic datasets.Results: ChiBE is a free, open-source software tool for visualizing, querying, and analyzing human biological pathways in BioPAX format. The recently released version 2 can search for neighborhoods, paths between molecules, and common regulators/targets of molecules, on large integrated cellular networks in the Pathway Commons database as well as in local BioPAX models. Resulting networks can be automatically laid out for visualization using a graphically rich, process-centric notation. Profiling data from the cBioPortal for Cancer Genomics and expression data from the Gene Expression Omnibus can be overlaid on these networks.Conclusions: ChiBE's new capabilities are organized around a genomics-oriented workflow and offer a unique comprehensive pathway analysis solution for genomics researchers. The software is freely available at http://code.google.com/p/chibe. © 2014 Babur et al.; licensee BioMed Central Ltd.
Open Access
A link-based storage scheme for efficient aggregate query processing on clustered road networks
(Elsevier Ltd, 2010) Demir, E.; Aykanat, Cevdet; Cambazoglu, B. B.
The need to have efficient storage schemes for spatial networks is apparent when the volume of query processing in some road networks (e.g., the navigation systems) is considered. Specifically, under the assumption that the road network is stored in a central server, the adjacent data elements in the network must be clustered on the disk in such a way that the number of disk page accesses is kept minimal during the processing of network queries. In this work, we introduce the link-based storage scheme for clustered road networks and compare it with the previously proposed junction-based storage scheme. In order to investigate the performance of aggregate network queries in clustered road networks, we extend our recently proposed clustering hypergraph model from junction-based storage to link-based storage. We propose techniques for additional storage savings in bidirectional networks that make the link-based storage scheme even more preferable in terms of the storage efficiency. We evaluate the performance of our link-based storage scheme against the junction-based storage scheme both theoretically and empirically. The results of the experiments conducted on a wide range of road network datasets show that the link-based storage scheme is preferable in terms of both storage and query processing efficiency. © 2009 Elsevier B.V. All rights reserved.
Open Access
Looking for timing variations in the transits of 16 exoplanets
(Oxford University Press, 2024-04-05) Yalcinkaya, S.; Esmer, E. M.; Basturk, O.; Muhaymin, A.; Kutluay, A. C.; Silistre, D. I.; Akar, F.; Southworth, J.; Mancini, L.; Davoudi, F.; Karamanli, E.; Tezcan, F.; Demir, E.; Yilmaz, D.; Guleroglu, E.; Tekin, M.; Taskin, I.; Aladag, Y.; Sertkan, E.; Kurt, U. Y.; Fisek, S.; Kaptan, S.; Alis, S.; Aksaker, N.; Yelkenci, F. K.; Tezcan, C. T.; Kaya, A.; Oglakkaya, D.; Aydin, Z. S.; Yesilyaprak, C.
We update the ephemerides of 16 transiting exoplanets using our ground-based observations, new Transiting Exoplanet Survey Satellite data, and previously published observations including those of amateur astronomers. All these light curves were modelled by making use of a set of quantitative criteria with the exofast code to obtain mid-transit times. We searched for statistically significant secular and/or periodic trends in the mid-transit times. We found that the timing data are well modelled by a linear ephemeris for all systems except for XO-2 b, for which we detect an orbital decay with the rate of -12.95 +/- 1.85 ms yr(-1) that can be confirmed with future observations. We also detect a hint of potential periodic variations in the transit timing variation data of HAT-P-13 b, which also requires confirmation with further precise observations.
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, Uğur
Motivation 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.
Open Access
Pathway commons 2019 update: integration, analysis and exploration of pathway data
(Oxford University Press, 2020) Rodchenkov, I.; Babur, Ö.; Luna, A.; Aksoy, B. A.; Wong, J. V.; Fong, D.; Franz, M.; Siper, M. C.; Cheung, M.; Wrana, M.; Mistry, H.; Mosier, L.; Dlin, J.; Wen, Q.; O’Callaghan, C.; Li, W.; Elder, G.; Smith, P. T.; Dallago, C.; Cerami, E.; Gross, B.; Doğrusöz, Uğur; Demir, E.; Bader, G. D.; Sander, C.
Pathway Commons (https://www.pathwaycommons.org) is an integrated resource of publicly available information about biological pathways including biochemical reactions, assembly of biomolecular complexes, transport and catalysis events and physical interactions involving proteins, DNA, RNA, and small molecules (e.g. metabolites and drug compounds). Data is collected from multiple providers in standard formats, including the Biological Pathway Exchange (BioPAX) language and the Proteomics Standards Initiative Molecular Interactions format, and then integrated. Pathway Commons provides biologists with (i) tools to search this comprehensive resource, (ii) a download site offering integrated bulk sets of pathway data (e.g. tables of interactions and gene sets), (iii) reusable software libraries for working with pathway information in several programming languages (Java, R, Python and Javascript) and (iv) a web service for programmatically querying the entire dataset. Visualization of pathways is supported using the Systems Biological Graphical Notation (SBGN). Pathway Commons currently contains data from 22 databases with 4794 detailed human biochemical processes (i.e. pathways) and ∼2.3 million interactions. To enhance the usability of this large resource for end-users, we develop and maintain interactive web applications and training materials that enable pathway exploration and advanced analysis.
Open Access
SBGNViz: A tool for visualization and complexity management of SBGN process description maps
(Public Library of Science, 2015) Sari, M.; Bahceci I.; Dogrusoz, U.; Sumer, S.O.; Aksoy, B.A.; Babur O.; Demir, E.
Background Information about cellular processes and pathways is becoming increasingly available in detailed, computable standard formats such as BioPAX and SBGN. Effective 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 viewers that support these platforms and other use cases. Results Towards this goal, we developed a web based viewer named SBGNViz for process description maps in SBGN (SBGN-PD). SBGNViz can visualize both BioPAX and SBGN formats. Unique features of SBGNViz include the ability to nest nodes to arbitrary depths to represent molecular complexes and cellular locations, automatic pathway layout, editing and highlighting facilities to enable focus on sub-maps, and the ability to inspect pathway members for detailed information from EntrezGene. SBGNViz can be used within a web browser without any installation and can be readily embedded into web pages. SBGNViz has two editions built with ActionScript and JavaScript. The JavaScript edition, which also works on touch enabled devices, introduces novel methods for managing and reducing complexity of large SBGN-PD maps for more effective analysis. Conclusion SBGNViz fills an important gap by making the large and fast-growing corpus of rich pathway information accessible to web based platforms. SBGNViz can be used in a variety of contexts and in multiple scenarios ranging from visualization of the results of a single study in a web page to building data analysis platforms. © 2015 Sari et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Software support for SBGN maps: SBGN-ML and LibSBGN
(Oxford University Press, 2012) Iersel, Martijn P. van; Villéger, A. C.; Czauderna, T.; Boyd, S. E.; Bergmann, F. T.; Luna, A.; Demir, E.; Sorokin, A.; Dogrusoz, U.; Matsuoka, Y.; Funahashi, A.; Aladjem, M. I.; Mi, H.; Moodie, S. L.; Kitano, H.; Le novère, N.; Schreiber, F.
Motivation: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner. © The Author(s) 2012. Published by Oxford University Press.