Abstract
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation.Database URL: http://causalbionet.com
Highlights
A paradigm shift in data generation and collection, and the growing number of scientific journals published have contributed to the exponential rate of growth in peer-reviewed publications
We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context
The website accesses a MongoDB, which stores all versions of the networks as JavaScript Object Notation (JSON) objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest
Summary
A paradigm shift in data generation and collection, and the growing number of scientific journals published have contributed to the exponential rate of growth in peer-reviewed publications. The CBN collection is organized into the following biological areas (Figure 1): cell response to stress, cell proliferation, cell fate (including DNA damage response, autophagy, senescence, apoptosis and necroptosis), tissue repair and angiogenesis, pulmonary inflammatory processes, vascular inflammatory processes and chronic obstructive pulmonary disease (COPD)specific networks. Details of these network models have been published previously [7,8,9,10,11,12]. The basic concept of BEL is the conversion of prior knowledge derived from either the literature or content-rich biological data sets to a common
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