Browsing by Subject "Systems biology"
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Item Open Access A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance(Frontiers Media S.A., 2023-06-22) Mazein, A.; Acencio, M. L.; Balaur, I.; Rougny, A.; Welter, D.; Niarakis, A.; Ramirez Ardila, D.; Doğrusöz, Uğur; Gawron, P.; Satagopam, V.; Gu, W.; Kremer, A.; Schneider, R.; Ostaszewski, M.As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.Item 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, UğurCausalPath (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.Item Open Access Efficient querying of SBGN maps stored in a graph database(Bilkent University, 2019-02) Karaca, Mustafa EnesGraph visualization is an important research area that endeavors to make graphs more understandable and easier to analyze. In various domains, graph visualization techniques and standards are developed to effectively analyze underlying graph based data. Systems Biology Graphical Notation (SBGN) is a standard language for modeling biological processes and pathways through graph visualization. Information about SBGN maps can be stored in XML based SBGNML files. libSBGN is a Java/C++ library for reading, writing SBGN-ML and manipulating SBGN maps in an object-oriented manner. Graph databases store data in terms of a graph structure consisting nodes and their relationships. Performing a computation on graph data stored in a graph database by traversals is more e cient than accessing tabled data in relational databases through costly join operations. Neo4j is a prominent graph database that provides a proprietary language named Cypher for querying stored graph data. Neo4j allows writing user defined procedures in Java as plugins to improve capabilities of Neo4j with third party Java libraries. With this thesis, we enable modeling SBGN maps in Neo4j graph database with support for compound structures. Using this SBGN data model in Neo4j, we developed graph based user defined procedures in Java using libSBGN as a plugin to Neo4j. These procedures were used to implement graph query algorithms, such as neighborhood, common stream, and paths between, along with helper functions such as populating a database from an SBGN map and loading an SBGN map from a graph database. These user defined procedures are designed to produce or consume SBGN-ML; hence, they can be used by any visualization tool which can import/export SBGN-ML text. Newt, a web based editor for viewing and diting SBGN maps, is such a tool making use of these procedures and hosting a local Neo4j instance by providing a web service to execute Cypher statements.Item Open Access Libraries and tools for viewing and editing biological maps in SBGN(Bilkent University, 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 Lower connectivity of tumor coexpression networks is not specific to cancer(IOP, 2019-05) Dalgıç, E.; Konu, Özlen; Safi Öz, Z.; Chan, C.Global level network analysis of molecular links is necessary for systems level view of complex diseases like cancer. Using genome-wide expression datasets, we constructed and compared gene co-expression based specific networks of pre-cancerous tumors (adenoma) and cancerous tumors (carcinoma) with paired normal networks to assess for any possible changes in network connectivity. Previously, loss of connectivity was reported as a characteristic of cancer samples. Here, we observed that pre-cancerous conditions also had significantly less connections than paired normal samples. We observed a loss of connectivity trend for colorectal adenoma, aldosterone producing adenoma and uterine leiomyoma. We also showed that the loss of connectivity trend is not specific to positive or negative correlation based networks. Differential hub genes, which were the most highly differentially less connected genes in tumor, were mostly different between different datasets. No common gene list could be defined which underlies the lower connectivity of tumor specific networks. Connectivity of colorectal cancer methylation targets was different from other genes. Extracellular space related terms were enriched in negative correlation based differential hubs and common methylation targets of colorectal carcinoma. Our results indicate a systems level change of lower connectivity as cells transform to not only cancer but also pre-cancerous conditions. This systems level behavior could not be attributed to a group of genes.Item Open Access Pathway activity inference using microarray data(Bilkent Center for Bioinformatics (BCBI), 2004) Babur, Özgün; Demir, Emek; Ayaz, Aslı; Doğrusöz, Uğur; Sakarya, OnurMotivation: Microarray technology provides cell-scale expression data; however, analyzing this data is notoriously difficult. It is becoming clear that system-oriented methods are needed in order to best interpret this data. Combining microarray expression data with previously built pathway models may provide useful insight about the cellular machinery and reveal mechanisms that govern diseases. Given a qualitative state - transition model of the cellular network and an expression profile of RNA molecules, we would like to infer possible differential activity of the other molecules such as proteins on this network. Results: In this paper an efficient algorithm using a new approach is proposed to attack this problem. Using the regulation relations on the network, we determine possible scenarios that might lead to the expression profile, and qualitatively infer the activity differences of the molecules between test and control samples. Availability: This new analysis method has been implemented as part of a microarray data analysis component within PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition), which is a software environment for pathway storage, integration and analysis. Facilities for easy analysis and visualization of the results is also provided. Contact: http://www.patika.org.Item Open Access PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization(Oxford University Press, 2006-02-01) Doğrusöz, Uğur; Erson, E. Zeynep; Giral, Erhan; Demir, Emek; Babur, Özgün; Çetintaş, Ahmet; Çolak, RecepSummary: PATIKAweb provides a Web interface for retrieving and analyzing biological pathways in the PATIKA database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats. © The Author 2005. Published by Oxford University Press. All rights reserved.Item Open Access Semantic validation of biological maps in SBGN(Bilkent University, 2019-09) Çalış, Umut UtkuGraph visualization is a research field where relational information is graphically represented in the form of graphs or networks. It is applicable in numerous areas from computer network systems, to biology, to software engineering. In such areas, graph visualization techniques provide effective visual analysis of graph based data. Systems Biology Graphical Notation (SBGN) facilitates a standard model for representing biological entities and their interactions by using graph visualization. SBGN-ML is an XML based format for keeping information about SBGN maps. libSBGN enables writing and reading SBGN-ML files in an easy manner and is meant to bring syntactic and semantic validation to SBGN maps. It is currently available in Java/C++ (libSBGN) and JavaScript (libSBGN.js) programming languages with varying support for aforementioned. libSBGN enables important syntactic and semantic correctness concepts for manipulating SBGN maps and converting SBGN-ML files into several other formats. Syntactic validation of SBGN-ML files involves using a simple XML Schema Definition (XSD) file. This validation checks whether files are in correct form or not. However, this XSD file does not enable checking against semantic rules. For semantic validation of such files, the Schematron language was developed providing higher level semantic rule controls. With this thesis, we first enabled high level semantic validation (schematron validation) of SBGN maps in libSBGN.js, which uses XSLT and transformation of process description maps in SBGN-ML files. By using Schematron rules which are written in XPath syntax and enabling human-readable messages of validation errors and source of errors, we developed an XSLT stylesheet. We obtained validation result report by transforming SBGN-ML files using this XSLT stylesheet. In the JavaScript version of libSBGN library, we used a web based XSLT processor for transformation; hence, this library is now available for providing schematron validation in any SBGN related software. Furthermore, we added schematron validation checks to Newt, a web based SBGN pathway editor, using the updated libSBGN.js library. With this addition, Newt is now able to show validation results not only in a human-readable message text for the current map but also highlights the invalid map objects graphically, and, where appropriate, suggests a way to fix the problem automatically.Item 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.Item Open Access The systems biology graphical notation(Nature Publishing Group, 2009-08) Le Novère, N.; Hucka, M.; Mi, H.; Moodie, S.; Schreiber, F.; Sorokin, A.; Demir, Emek; Wegner, K.; Aladjem, M. I.; Wimalaratne, S. M.; Bergman, F. T.; Gauges, R.; Ghazal, P.; Kawaji, H.; Li, L.; Matsuoka, Y.; Villéger, A.; Boyd, S. E.; Calzone, L.; Courtot, M.; Doğrusöz, Uğur; Freeman, T. C.; Funahashi, A.; Ghosh, S.; Jouraku, A.; Kim, S.; Kolpakov, F.; Luna, A.; Sahle, S.; Schmidt, E.; Watterson, S.; Wu, G.; Goryanin, I.; Kell, D. B.; Sander, C.; Sauro, H.; Snoep, J. L.; Kohn, K.; Kitano, H.Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. © 2009 Nature America, Inc.Item Open Access Systems biology graphical notation markup language (SBGNML) version 0.3(De Gruyter, 2020) Luna, A.; Bergmann, F. T.; Czauderna, T.; Doğrusöz, Uğur; Rougny, A.; Dräger, A.; Touré, V.; Mazein, A.; Mazein, M. L.This document defines Version 0.3 Markup Language (ML) support for the Systems Biology Graphical Notation (SBGN), a set of three complementary visual languages developed for biochemists, modelers, and computer scientists. SBGN aims at representing networks of biochemical interactions in a standard, unambiguous way to foster efficient and accurate representation, visualization, storage, exchange, and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. SBGN is defined neutrally to programming languages and software encoding; however, it is oriented primarily towards allowing models to be encoded using XML, the eXtensible Markup Language. The notable changes from the previous version include the addition of attributes for better specify metadata about maps, as well as support for multiple maps, sub-maps, colors, and annotations. These changes enable a more efficient exchange of data to other commonly used systems biology formats (e. g., BioPAX and SBML) and between tools supporting SBGN (e. g., CellDesigner, Newt, Krayon, SBGN-ED, STON, cd2sbgnml, and MINERVA). More details on SBGN and related software are available at http://sbgn.org. 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.Item Open Access Systems biology graphical notation: process description language Level 1 Version 2.0(De Gruyter, 2019) Rougny, A.; Touré, V.; Moodie, S.; Balaur, I.; Czauderna, T.; Borlinghaus, H.; Doğrusöz, Uğur; Mazein, A.; Dräger, A.; Blinov, M. L.; Villéger, A.; Haw, R.; Demir, E.; Mi, H.; Sorokin, A.; Schreiber, F.; Luna, A.The Systems Biology Graphical Notation (SBGN) is an international community effort that aims to standardise the visualisation of pathways and networks for readers with diverse scientific backgrounds as well as to support an efficient and accurate exchange of biological knowledge between disparate research communities, industry, and other players in systems biology. SBGN comprises the three languages Entity Relationship, Activity Flow, and Process Description (PD) to cover biological and biochemical systems at distinct levels of detail. PD is closest to metabolic and regulatory pathways found in biological literature and textbooks. Its well-defined semantics offer a superior precision in expressing biological knowledge. PD represents mechanistic and temporal dependencies of biological interactions and transformations as a graph. Its different types of nodes include entity pools (e.g. metabolites, proteins, genes and complexes) and processes (e.g. reactions, associations and influences). The edges describe relationships between the nodes (e.g. consumption, production, stimulation and inhibition). This document details Level 1 Version 2.0 of the PD specification, including several improvements, in particular: 1) the addition of the equivalence operator, subunit, and annotation glyphs, 2) modification to the usage of submaps, and 3) updates to clarify the use of various glyphs (i.e. multimer, empty set, and state variable).Item Open Access Targeting mirna-protein regulatory networks to enhance chemotherapy response in BRCA1-mutated TNBCs(Bilkent University, 2016-09) Eyüpoğlu, ErolBreast cancer is the second most common cancer and the leading cause of cancer associated deaths in women worldwide. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. BRCA1-mutated TNBC patients generally respond well to DNA cross-linking agents like Cisplatin. However, most of the patients acquire resistance and eventually die. Therefore, there is a dire need of developing promising approaches to enhance chemo-response, hence, extending the survival of TNBC patients. MicroRNAs (miRNAs) play active role in controlling proliferation, apoptosis, invasion and drug resistance in cancer. However, the role of miRNA-protein interactions as a regulatory network in determining chemotherapy response of TNBCs has not been elucidated yet. Thus, we aimed to delineate miRNAs and miRNA-protein regulatory networks controlling chemotherapy resistance/response in BRCA1–mutated TNBCs. We firstly confirmed that BRCA1-mutated breast cancer cells are more sensitive to Cisplatin as compared to BRCA1-competent cells. Afterwards, developing acquired chemotherapy resistant cell line model and using next generation sequencing technology (both miR-Seq and RNA-Seq), we have unravelled that p53 signalling is the upstream regulator of Cisplatin resistance. Moreover, with the use of Ingenuity Pathway Anlaysis (IPA) which uses omics data from a variety of experimental platforms, we analyzed, combined and modelled miRNA-mRNA interactions regulating Cisplatin resistance for the first time in a network manner. Interestingly, we identifed several network motifs e.g. coherent and incoherent feedforward loops centered around p53 protein which need further experimental validations. Again for the first time, this study has reported the re-sensitization effect of miR-455 family on Cisplatin resistance in breast cancer. Overall, findings of this study might be used as an alternative strategy for treatment of BRCA1-mutated TNBCs by modulating miRNAs and their targets to re-sensitize Cisplatin resistant tumors.