Abstract
A rapidly growing corpus of formal, computable pathway information can be used to answer important biological questions including finding non-trivial connections between cellular processes, identifying significantly altered portions of the cellular network in a disease state and building predictive models that can be used for precision medicine. Due to its complexity and fragmented nature, however, working with pathway data is still difficult. We present Paxtools, a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language. Paxtools allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information. Paxtools can run on any platform that has a Java Runtime Environment and was tested on most modern operating systems. Paxtools is open source and is available under the Lesser GNU public license (LGPL), which allows users to freely use the code in their software systems with a requirement for attribution. Source code for the current release (4.2.0) can be found in Software S1. A detailed manual for obtaining and using Paxtools can be found in Protocol S1. The latest sources and release bundles can be obtained from biopax.org/paxtools.
Highlights
The total volume of computational pathway data mapped by biologists has entered a rapid growth phase
Pathway analysis has been used to determine genetically altered pathways in diverse cancer types [2,3], predict the functions and phenotypic effects of previously uncharacterized cancer genes [4,5], prioritize candidate genes and pathways for functional validation in model systems [6,7], identify network biomarkers correlated with clinical outcome in human disease [5], and translate genomic information into new targeted clinical applications [8]
A BioPAX record includes pathways, interactions, reactions and their participants. These elements are implemented as Java beans that have methods to access and manipulate the properties as described in BioPAX specification
Summary
The total volume of computational pathway data mapped by biologists has entered a rapid growth phase. There are two key technical challenges we need to address to streamline the use of this rapidly expanding information : (i) standardizing and integrating pathway data from multiple heterogeneous sources and (ii) developing methods and tools that can help scientists access, map and analyze pathway information. The second key challenge is to build methods, algorithms and software tools to work with pathway data to answer biological questions [18,19,20,21].
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