MOTIVATION: Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. RESULTS: To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene function annotation is important for a variety of downstream analyses of genetic data. But experimental characterization of function remains costly and slow, making computational prediction an important endeavor. Phylogenetic approaches to prediction have been developed, but implementation of a practical Bayesian framework for parameter estimation remains an outstanding challenge. We have developed a computationally efficient model of evolution of gene annotations using phylogenies based on a Bayesian framework using Markov Chain Monte Carlo for parameter estimation. Unlike previous approaches, our method is able to estimate parameters over many different phylogenetic trees and functions. The resulting parameters agree with biological intuition, such as the increased probability of function change following gene duplication. The method performs well on leave-one-out cross-validation, and we further validated some of the predictions in the experimental scientific literature.

MOTIVATION: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner. AVAILABILITY AND IMPLEMENTATION: Milestone 2 was released in December 2011. Source code, example files and binaries are freely available under the terms of either the LGPL v2.1+ or Apache v2.0 open source licenses from http://libsbgn.sourceforge.net. CONTACT: [email protected].

MOTIVATION: BioPAX is a standard language for representing and exchanging models of biological processes at the molecular and cellular levels. It is widely used by different pathway databases and genomics data analysis software. Currently, the primary source of BioPAX data is direct exports from the curated pathway databases. It is still uncommon for wet-lab biologists to share and exchange pathway knowledge using BioPAX. Instead, pathways are usually represented as informal diagrams in the literature. In order to encourage formal representation of pathways, we describe a software package that allows users to create pathway diagrams using CellDesigner, a user-friendly graphical pathway-editing tool and save the pathway data in BioPAX Level 3 format. AVAILABILITY: The plug-in is freely available and can be downloaded at ftp://ftp.pantherdb.org/CellDesigner/plugins/BioPAX/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.