Ondex Web: web-based visualization and exploration of heterogeneous biological networks

Taubert, Jan; Hassani‐Pak, Keywan; Castells-Brooke, Nathalie; Rawlings, Christopher J.

doi:10.1093/bioinformatics/btt740

Cited by 12 publications

(10 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…KnetMiner [10] (http://knetminer.rothamsted.ac.uk) is developed for investigating relationships between genes and phenotypes and for eQTL1Expression Quantitative Trait Locus. search. KnetMiner is based on Ondex [14], now integrates over 25 data sources and covers many organisms including human. Also, KnetMiner can be used for gene prioritization: takes phenotype and optionally a list of candidates and scores them on the basis of previous knowledge.…”

Section: Related Workmentioning

confidence: 99%

GenCoNet – A Graph Database for the Analysis of Comorbidities by Gene Networks

Shoshi

Hofestädt

Zolotareva

et al. 2018

Journal of Integrative Bioinformatics

View full text Add to dashboard Cite

The prevalence of comorbid diseases poses a major health issue for millions of people worldwide and an enormous socio-economic burden for society. The molecular mechanisms for the development of comorbidities need to be investigated. For this purpose, a workflow system was developed to aggregate data on biomedical entities from heterogeneous data sources. The process of integrating and merging all data sources of the workflow system was implemented as a semi-automatic pipeline that provides the import, fusion, and analysis of the highly connected biomedical data in a Neo4j database GenCoNet. As a starting point, data on the common comorbid diseases essential hypertension and bronchial asthma was integrated. GenCoNet (https://genconet.kalis-amts.de) is a curated database that provides a better understanding of hereditary bases of comorbidities.

show abstract

Section: Related Workmentioning

confidence: 99%

GenCoNet – A Graph Database for the Analysis of Comorbidities by Gene Networks

Shoshi

Hofestädt

Zolotareva

et al. 2018

Journal of Integrative Bioinformatics

View full text Add to dashboard Cite

show abstract

“…Previously, our group developed a web-based tool, Ondex Web ( Taubert et al , 2014), for visualising knowledge networks generated with the Ondex data integration platform ( Kohler et al , 2006). It supported the Ondex exchange language (OXL) and was predominantly used to visualise a biological knowledge domain.…”

Section: Introductionmentioning

confidence: 99%

KnetMaps: a BioJS component to visualize biological knowledge networks

2018

View full text Add to dashboard Cite

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

show abstract

“…This enables an exploratory analysis: starting with a small network and then gradually, on-demand, extending to a larger network. A web-enabled version of the Ondex UI, called Ondex Web, has been developed to allow Ondex network visualisations to be embedded in web-pages (Taubert et al, 2014). Furthermore, a Cytoscape plugin, called OndexView allows for concise graphical representations of integrated knowledge networks (Weile et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Developing integrated crop knowledge networks to advance candidate gene discovery

Hassani‐Pak

Castellote

Esch

et al. 2016

Applied & Translational Genomics

View full text Add to dashboard Cite

The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

show abstract

Ondex Web: web-based visualization and exploration of heterogeneous biological networks

Cited by 12 publications

References 8 publications

GenCoNet – A Graph Database for the Analysis of Comorbidities by Gene Networks

GenCoNet – A Graph Database for the Analysis of Comorbidities by Gene Networks

KnetMaps: a BioJS component to visualize biological knowledge networks

Developing integrated crop knowledge networks to advance candidate gene discovery

Contact Info

Product

Resources

About