Reference environment for the manuscript [Network link prediction by global silencing of indirect correlations](http://dx.doi.org/10.1038/nbt.2601) Nat. Biotechnol. 31, 720–5 (2013)
DANIEL HURLEY
Baruch Barzel
Albert-Lászlo Barabási
DAVID BUDDEN
Edmund Crampin
JOSEPH CURSONS
Matt Faria
10.4225/49/55DA8FA8CE707
https://melbourne.figshare.com/articles/software/Reference_environment_bootable_ISO_for_the_paper_Network_link_prediction_by_global_silencing_of_indirect_correlations_Barzel_et_al_2013_/2002314
### Overview<br><br>This is the reference environment for the manuscript ['Network link prediction by global silencing of indirect correlations'](https://dx.doi.org/10.1038/nbt.2601). It executes code to reproduce specific results described in the manuscript. You can find more information about this research at the GitHub repository for the code(https://github.com/baruchbarzel/NatureBiotech-31-720.git). <br><br>To find other versions of this reference environment, see Other Links below. To learn more about reference environments, [see the detailed description here](https://uomsystemsbiology.github.io/reference-environments/). <br><br>### Instructions for use<br><br>This version of the reference environment is a live image as a bootable read-only ISO. To use it:<br><br>- Install a virtualization tool like [VirtualBox](https://www.virtualbox.org/), then <br>- Create a new virtual machine in the virtualization tool with a virtual CD/DVD-ROM drive<br>- Mount the ISO in the drive<br>- Boot the machine. <br><br>This will start a virtual machine with scripts to run which reproduce results described in the manuscript. <br><br>### Other links<br><br>[Manuscript link](https://dx.doi.org/10.1038/nbt.2601)<br><br>[Project page link](https://github.com/baruchbarzel/NatureBiotech-31-720.git)<br><br>[Docker container](https://hub.docker.com/r/uomsystemsbiology/barzel2013network/)<br><br>[Vagrant-managed virtual machine](https://github.com/uomsystemsbiology/barzel2013network_reference_environment)<br><br><br>
2015-08-26 04:09:06
Reference environments
Computational Biology
Systems Biology
Computational Biology
Systems Biology