Title |
Using Biological Pathway Data with Paxtools
|
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Published in |
PLoS Computational Biology, September 2013
|
DOI | 10.1371/journal.pcbi.1003194 |
Pubmed ID | |
Authors |
Emek Demir, Özgün Babur, Igor Rodchenkov, Bülent Arman Aksoy, Ken I. Fukuda, Benjamin Gross, Onur Selçuk Sümer, Gary D. Bader, Chris Sander |
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. |
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India | 2 | 10% |
United Kingdom | 1 | 5% |
Japan | 1 | 5% |
Chile | 1 | 5% |
Canada | 1 | 5% |
France | 1 | 5% |
Unknown | 9 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 10 | 50% |
Members of the public | 8 | 40% |
Science communicators (journalists, bloggers, editors) | 2 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 6% |
United Kingdom | 5 | 4% |
Germany | 2 | 2% |
France | 2 | 2% |
Spain | 2 | 2% |
Brazil | 1 | <1% |
Canada | 1 | <1% |
Mexico | 1 | <1% |
Korea, Republic of | 1 | <1% |
Other | 2 | 2% |
Unknown | 92 | 79% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 39 | 34% |
Student > Ph. D. Student | 37 | 32% |
Other | 7 | 6% |
Student > Master | 7 | 6% |
Professor > Associate Professor | 6 | 5% |
Other | 12 | 10% |
Unknown | 8 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 49 | 42% |
Biochemistry, Genetics and Molecular Biology | 23 | 20% |
Computer Science | 19 | 16% |
Medicine and Dentistry | 6 | 5% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
Other | 7 | 6% |
Unknown | 10 | 9% |