Browsing by Subject "Computational biology."

Now showing 1 - 4 of 4

Open Access
Causality analysis in biological networks
(2010) Babur, Özgün
Systems biology is a rapidly emerging field, shaped in the last two decades or so, which promises understanding and curing several complex diseases such as cancer. In order to get an insight about the system – specifically the molecular network in the cell – we need to work on following four fundamental aspects: experimental and computational methods to gather knowledge about the system, mathematical models for representing the knowledge, analysis methods for answering questions on the model, and software tools for working on these. In this thesis, we propose new approaches related to all these aspects. In this thesis, we define new terms and concepts that helps us to analyze cellular processes, such as positive and negative paths, upstream and downstream relations, and distance in process graphs. We propose algorithms that will search for functional relations between molecules and will answer several biologically interesting questions related to the network, such as neighborhoods, paths of interest, and common targets or regulators of molecules. In addition, we introduce ChiBE, a pathway editor for visualizing and analyzing BioPAX networks. The tool converts BioPAX graphs to drawable process diagrams and provides the mentioned novel analysis algorithms. Users can query pathways in Pathway Commons database and create sub-networks that focus on specific relations of interest. We also describe a microarray data analysis component, PATIKAmad, built into ChiBE and PATIKAweb, which integrates expression experiment data with networks. PATIKAmad helps those tools to represent experiment values on network elements and to search for causal relations in the network that potentially explain dependent expressions. Causative path search depends on the presence of transcriptional relations in the model, which however is underrepresented in most of the databases. This is mainly due to insufficient knowledge in the literature. We finally propose a method for identifying and classifying modulators of transcription factors, to help complete the missing transcriptional relations in the pathway databases. The method works with large amount of expression data, and looks for evidence of modulation for triplets of genes, i.e. modulator - factor - target. Modulator candidates are chosen among the interacting proteins of transcription factors. We expect to observe that expression of the target gene depends on the interaction between factor and modulator. According to the observed dependency type, we further classify the modulation. When tested, our method finds modulators of Androgen Receptor; our top-scoring result modulators are supported by other evidence in the literature. We also observe that the modulation event and modulation type highly depend on the specific target gene. This finding contradicts with expectations of molecular biology community who often assume a modulator has one type of effect regardless of the target gene.
Open Access
Integrating biological pathways and genomic profiles with ChiBE 2
(2013) Çakır, Merve
Biological pathways store information about spatial and temporal organization of interactions taking place in an organism. They hold valuable information that can assist scientific community in understanding the details of a particular mechanism or deciphering the reasons of disruption when the system goes wrong. However, extracting knowledge from these pathways is not trivial as they can be huge and complicated. Additionally, simple visualization of pathways will only reveal limited knowledge, whereas their integration with experimental results can identify distinct and intriguing relationships. Therefore, it is critical to have tools that are specialized in analyzing and understanding biological pathways. ChiBE is one such tool that can visualize, manipulate and analyze pathway data stored in BioPAX format. While preparing the second version of the tool, there have been improvements regarding pathway searches, high throughput data integration, and database connections. Visual notation has also been updated in order to follow standards in visualizations defined by the SBGN community. Previously defined pathway query algorithms have been adapted to be compatible with the BioPAX model. New query types have also been designed to offer a wider range of options. With these queries, ChiBE now offers a variety of ways of pathway decomposition and thorough analysis of complex pathway views. There has also been improvements in integration of high throughput experimental results. To offer easy access to expression microarrays, a gateway to the GEO database has been added. The cBio Cancer Genomics Portal is also now reachable within ChiBE in order to obtain information about genomic status of various cancer cells. After simply asking for an identifier of a particular experiment, ChiBE retrieves the results from databases and then integrates them with the available pathway view through color codes. Furthermore, a connection to DAVID database is available, in case users want to annotate a list of genes with respect to biological terms associated with them. With these new features and improvements, ChiBE 2 has become a comprehensive tool that offers a wide range of analysis options with a genomics-oriented workflow to deepen our understanding of biological pathways.
Open Access
Methods and tools for visualization and management of SBGN process description maps
(2014) Sarı, Mecit
Graphs are commonly used to model relational information in many areas such as relational databases, software engineering, biological and social networks. In visualization of graphs, automatic layout, interactive editing and complexity management of crowded graphs are essential for effective utilization of underlying information. Advances in graphical user interfaces have given rise and value to interactive editing and diagramming techniques in graph visualization. As the size of the information to be visualized vastly increased, it became harder to analyze such networks, making use of relational information needed to be acquired. To overcome this problem, sophisticated and domain-specific complexity management techniques should be provided. The Systems Biology Graphical Notation (SBGN) has been developed over a number of years by biochemists and computer scientists to standardize visual representation of biochemical and cellular processes. SBGN introduces a concrete, detailed set of symbols for scientists to represent network of interactions, in a way that is not open to more than one interpretation. It also describes the manner, in which such graphical information should be interpreted. The SBGN Process Description (PD) language shows how entities are influenced by processes, which are represented by several reaction types in a biological pathway. It can be used to show all the molecular interactions taking place in a network of biochemical entities, with the same entity appearing multiple times in the same diagram. We developed methods and tools to effectively visualize and manage SBGNPD diagrams. Specifically, we introduced new algorithms for proper management of complexity of large SBGN-PD diagrams. These algorithms strive to keep SBGN-PD diagrams intact as complexity management takes places. In addition, we provided software components and web-based tools that implement these methods. These tools use state-of-the-art web technologies and libraries.
Open Access
VISIBIOweb : a web-based visualization and layout service for biological pathways
(2009) Dilek, Alptuğ
A biological pathway is a representation of biological reactions between molecules in a living cell. At present, there are hundreds of Internet-accessible databases storing biological pathway data. Exchanging, handling, and storing this data are crucial in terms of both providing understandability and allowing further enhancements on the gathered data. As a result of this necessity, many biological models were developed to cluster the data in a meaningful manner under a semantically reasonable hierarchy. As the amount and complexity of the data increases, visualization of pathways becomes inevitable. Graphs are inherently suitable for modeling pathways. The task of creating a visual representation for pathways dynamically requires methods from the area of graph visualization. As a result, many software systems, which can interpret the pathway data with a graph structure and visualize the constructed graph, emerged. However, many of these software systems are insufficient due to poor complexity handling of the underlying model, lack of visual standardization or long installation steps. In this thesis, we introduce VISIBIOweb, a new open-source and web-based visualization service for biological pathway models stored in BioPAX (Biological Pathways Exchange Language) format. VISIBIOweb runs on Apache Tomcat server and is implemented in Java based on Eclipse GEF (Graphical Editing Framework). Google Maps API is used on the client side as the core component to visualize the representation constructed on the server. VISIBIOweb supports basic graph viewing functionalities such as zooming, scrolling, and selection of graph objects. The inspector window is provided to view the properties of the selected graph object. Once the view for the uploaded biological model is created, it can be stored as a static image. The biological models can also be persisted and embedded within other web sites just like Google Maps. The layout information of the constructed graph is also provided in an XML-based format. The introduction of such a format is a good starting point to develop an official layout extension for BioPAX format.