PathSys: integrating molecular interaction graphs for systems biology

Baitaluk, Michael; Qian, Xufei; Godbole, Shubhada; Raval, Alpan; Ray, Animesh; Gupta, Amarnath

doi:10.1186/1471-2105-7-55

Cited by 48 publications

(10 citation statements)

References 42 publications

(43 reference statements)

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“…al . data integrated (in A) ) into the IntegromeDB database and available to be analyzed in concert with wealth of other host-pathogen data available in BiologicalNetworks [ 40 - 42 ]. Host factors that were already present in our database and known to be related to viral response are colored green, whereas host factors newly discovered by Konig et.…”

Section: Resultsmentioning

confidence: 99%

“…In this paper, the approach at cross-scale data integration to study host-pathogen interactions is proposed and demonstrated on a study of the Influenza infection. The proposed system is an extension of the previously developed BiologicalNetworks [ 40 , 41 ] and IntegromeDB [ 42 ]. It represents a general-purpose graph warehouse with its own data definition and query language, augmented with data types for biological entities.…”

Section: Introductionmentioning

confidence: 99%

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BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

et al. 2011

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BackgroundUnderstanding of immune response mechanisms of pathogen-infected host requires multi-scale analysis of genome-wide data. Data integration methods have proved useful to the study of biological processes in model organisms, but their systematic application to the study of host immune system response to a pathogen and human disease is still in the initial stage.ResultsTo study host-pathogen interaction on the systems biology level, an extension to the previously described BiologicalNetworks system is proposed. The developed methods and data integration and querying tools allow simplifying and streamlining the process of integration of diverse experimental data types, including molecular interactions and phylogenetic classifications, genomic sequences and protein structure information, gene expression and virulence data for pathogen-related studies. The data can be integrated from the databases and user's files for both public and private use.ConclusionsThe developed system can be used for the systems-level analysis of host-pathogen interactions, including host molecular pathways that are induced/repressed during the infections, co-expressed genes, and conserved transcription factor binding sites. Previously unknown to be associated with the influenza infection genes were identified and suggested for further investigation as potential drug targets. Developed methods and data are available through the Java application (from BiologicalNetworks program at http://www.biologicalnetworks.org) and web interface (at http://flu.sdsc.edu).

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

et al. 2011

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“…Network models offer a powerful approach for the representation, integration, and analysis of the resulting data. Hence, the construction and analysis of genetic regulatory networks, 1 protein-protein interaction networks, metabolic networks, 2 and their combinations 3 , 4 are central concerns of systems biology. 1 – 10 Recent advances in systems biology have led to substantial progress on problems such as understanding the essential macromolecular sequence and structural features of molecular interactions; 11 extracting signaling pathways from gene and protein interaction networks; 12 , 13 discovering topological and other characteristics of these networks; 14 – 18 integration of disparate types of data (microarrays, proteomics, physical interaction, subcellular localization, etc.…”

Section: Introductionmentioning

confidence: 99%

BioNetwork Bench: Database and Software for Storage, Query, and Analysis of Gene and Protein Networks

Kohutyuk

Towfic

Greenlee

et al. 2012

Bioinform Biol Insights

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Gene and protein networks offer a powerful approach for integration of the disparate yet complimentary types of data that result from high-throughput analyses. Although many tools and databases are currently available for accessing such data, they are left unutilized by bench scientists as they generally lack features for effective analysis and integration of both public and private datasets and do not offer an intuitive interface for use by scientists with limited computational expertise. We describe BioNetwork Bench, an open source, user-friendly suite of database and software tools for constructing, querying, and analyzing gene and protein network models. It enables biologists to analyze public as well as private gene expression; interactively query gene expression datasets; integrate data from multiple networks; store and selectively share the data and results. Finally, we describe an application of BioNetwork Bench to the assembly and iterative expansion of a gene network that controls the differentiation of retinal progenitor cells into rod photoreceptors. The tool is available from http://bionetworkbench.sourceforge.net/BackgroundThe emergence of high-throughput technologies has allowed many biological investigators to collect a great deal of information about the behavior of genes and gene products over time or during a particular disease state. Gene and protein networks offer a powerful approach for integration of the disparate yet complimentary types of data that result from such high-throughput analyses. There are a growing number of public databases, as well as tools for visualization and analysis of networks. However, such databases and tools have yet to be widely utilized by bench scientists, as they generally lack features for effective analysis and integration of both public and private datasets and do not offer an intuitive interface for use by biological scientists with limited computational expertise.ResultsWe describe BioNetwork Bench, an open source, user-friendly suite of database and software tools for constructing, querying, and analyzing gene and protein network models. BioNetwork Bench currently supports a broad class of gene and protein network models (eg, weighted and un-weighted, undirected graphs, multi-graphs). It enables biologists to analyze public as well as private gene expression, macromolecular interaction and annotation data; interactively query gene expression datasets; integrate data from multiple networks; query multiple networks for interactions of interest; store and selectively share the data as well as results of analyses. BioNetwork Bench is implemented as a plug-in for, and hence is fully interoperable with, Cytoscape, a popular open-source software suite for visualizing macromolecular interaction networks. Finally, we describe an application of BioNetwork Bench to the problem of assembly and iterative expansion of a gene network that controls the differentiation of retinal progenitor cells into rod photoreceptors.ConclusionsBioNetwork Bench provides a suite of open ...

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“…A number of tools are being developed for interpreting and exploring large-scale biological networks, such as: PathSys [8] , NAViGaTOR [9] , BIOZON [10] , [11] , BN++ [12] , ONDEX [13] , Cytoscape, and Osprey [14] . For a review of visualization tools for systems biology see [15] .…”

Section: Introductionmentioning

confidence: 99%

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

et al. 2011

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The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation.

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PathSys: integrating molecular interaction graphs for systems biology

Cited by 48 publications

References 42 publications

BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

BiologicalNetworks - tools enabling the integration of multi-scale data for the host-pathogen studies

BioNetwork Bench: Database and Software for Storage, Query, and Analysis of Gene and Protein Networks

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

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