Abstract
Network inference utilizes experimental high-throughput data for the reconstruction of molecular interaction networks where new relationships between the network entities can be predicted. Despite the increasing amount of experimental data, the parameters of each modeling technique cannot be optimized based on the experimental data alone, but needs to be qualitatively assessed if the components of the resulting network describe the experimental setting. Candidate list prioritization and validation builds upon data integration and data visualization. The application of tools supporting this procedure is limited to the exploration of smaller information networks because the display and interpretation of large amounts of information is challenging regarding the computational effort and the users' experience. The Ondex software framework was extended with customizable context-sensitive menus which allow additional integration and data analysis options for a selected set of candidates during interactive data exploration. We provide new functionalities for on-the-fly data integration using InterProScan, PubMed Central literature search, and sequence-based homology search. We applied the Ondex system to the integration of publicly available data for Aspergillus nidulans and analyzed transcriptome data. We demonstrate the advantages of our approach by proposing new hypotheses for the functional annotation of specific genes of differentially expressed fungal gene clusters. Our extension of the Ondex framework makes it possible to overcome the separation between data integration and interactive analysis. More specifically, computationally demanding calculations can be performed on selected sub-networks without losing any information from the whole network. Furthermore, our extensions allow for direct access to online biological databases which helps to keep the integrated information up-to-date.
Highlights
In our study, we developed and applied customizable contextsensitive menus to the data integration and visualization tool Ondex
We have enhanced the features within Ondex by implementing customizable context-sensitive menus which allow interactive integration of additional data while exploring the integrated information network in the Ondex front-end
The precise workflow depends on intermediate results and the research focus of the experiment. This is the first application of an integrative network analysis approach to A. nidulans
Summary
We developed and applied customizable contextsensitive menus to the data integration and visualization tool Ondex This allows for the interactive exploration of experimental data that is integrated into an information network. A highly diverse variety of network inference modeling techniques have been developed based on differential equation systems or Bayesian networks (as reviewed in Hecker et al, 2009). The gene regulatory network inference method NetGenerator (Guthke et al, 2005; Töpfer et al, 2006; Weber et al, 2013) is based on differential equation systems which minimizes both the model fit error, i.e., the difference between the measured and the simulated data of time-series experiments, and the number of model parameters. Prior knowledge is used to guide the inference process (Linde et al, 2010, 2012)
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