Related Experiment Video
Updated: May 8, 2026
Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
Published on: March 7, 2018
Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting
Evan O Paull1, Daniel E Carlin, Mario Niepel
1Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064, Department of Systems Biology, HMS LINCS Center, Harvard Medical School, Boston, MA 02115 and Howard Hughes Medical Institute, Santa Cruz, CA 95064, USA.
Motivation:
Identifying the cellular wiring that connects genomic perturbations to transcriptional changes in cancer is essential to gain a mechanistic understanding of disease initiation, progression and ultimately to predict drug response. We have developed a method called Tied Diffusion Through Interacting Events (TieDIE) that uses a network diffusion approach to connect genomic perturbations to gene expression changes characteristic of cancer subtypes. The method computes a subnetwork of protein-protein interactions, predicted transcription factor-to-target connections and curated interactions from literature that connects genomic and transcriptomic perturbations.
Results:
Application of TieDIE to The Cancer Genome Atlas and a breast cancer cell line dataset identified key signaling pathways, with examples impinging on MYC activity. Interlinking genes are predicted to correspond to essential components of cancer signaling and may provide a mechanistic explanation of tumor character and suggest subtype-specific drug targets.
Availability:
Software is available from the Stuart lab's wiki: https://sysbiowiki.soe.ucsc.edu/tiedie.
Contact:
jstuart@ucsc.edu.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
