There is a newer version of the record available.

Published March 21, 2019 | Version v1
Dataset Open

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models

Creators

  • 1. Bioinformatics and Modelling, Luxembourg Institute of Health, and Mathematical Modelling of Cellular Processes, Max Delbrück Center for Molecular Medicine in the Helmholtz Association
  • 2. School of Computer Science and Engineering, Nanyang Technological University
  • 3. Bioinformatics and Modelling, Luxembourg Institute of Health

Description

Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1 and S2. Legends are included under each figure.

sbm-for-correlation-based-networks-master.zip: Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks.

Files

Baum_et_al_2019_Supplementary_Figures.pdf

Files (1.6 MB)

Name Size Download all
md5:ee8246bcb81ac40d7420e87e63755d7c
476.9 kB Preview Download
md5:aaa4496915ef5cade0586d0c9b122650
1.2 MB Preview Download

Additional details

References

  • Budczies J, Brockmoller SF, et al. (2013). Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J Proteomics. 2013;94:279-88.
  • Peixoto TP (2014). The graph-tool python library. 10.6084/m9.figshare.1164194