OpenBEL powers SBVImprover Challenge 3
OpenBEL powers SBVImprover Challenge 3. The goal of the Challenge is to perform peer review of a massive number of networks for lung biology. The key is using OpenBEL to represent the biology in a consistent open format that can be turned into a computationally tractable model.
Today, biological networks play a fundamental role in systems-based approaches to biology, pharmacology, and toxicology. With the shift from low-throughput technologies such as single gene PCR to the system-wide evaluation of transcriptomes, the size and number of datasets being deposited into databases has grown exponentially, as has the number of published scientific articles. Biological networks clearly and concisely encapsulate this large existing knowledge base. By depicting causal and correlative relationships (edges) between biological entities (nodes) in a way that is both computable and human-readable, biological networks provide a top-down view on collected data. This can aid the focused generation of hypotheses prior to the investigation of specific pathways. The network models were derived from data-driven approaches together with information captured from peer-reviewed literature. This resulted in 50 networks representing various aspects of lung biology.
Join the fun (http://bionet.sbvimprover.com) and maybe win a travel stipend to go to the followup Jamboree. See a novel and powerful approach for network biology peer review.
What is OpenBEL & How You Can Participate
In biotechnology and life sciences, the use of OpenBEL and its standard way of expressing information can accelerate the pace of technology innovation and scientific discovery in areas such as network visualization of neural brain function; understanding of complex inter-related disease biology; comparison of human diseases with various animal models; deep investigation of drug efficacy and toxicity; as well as development of innovative therapeutics and diagnostics for personalized healthcare.
The OpenBEL project advances these disciplines with the use of a common Biological Expression Language (BEL) that represents scientific findings in a computable form by capturing causal and correlative relationships in context. It also includes the BEL framework, an open platform designed to capture, integrate and store knowledge within an organization and with its partners. Central to the design of the framework is the ability to integrate knowledge across different representational vocabularies and ontologies. This allows organizations to combine knowledge from disparate sources into centralized knowledge repositories.
The combined knowledge can be made available to a variety of decision support and analytical applications through a standardized set of computable networks and APIs. To learn more about the OpenBEL Consortium and how your company can participate, please contact us.