TiCoNE

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TiCoNE

Time Course Network Enrichment

We developed time course network enrichment (TiCoNE), a novel human-augmented time series clustering method combined with a temporal network enricher that enables drug target discovery based on temporal networks. Temporal gene clusters are embedded into molecular networks, and TiCoNE identifies molecular pathways (subnetworks) with a differential behavior under two conditions (e.g., diseases). Such temporal disease pathway candidates are evaluated by calculating empirical p-values.

TiCoNE works with most kinds of biological entities (genes, proteins, RNAs, etc.) and most types of molecular measures acquirable for them (transcriptomics,proteomics, etc.). It comes as web server and as Cytoscape plugin.

Web: https://ticone.compbio.sdu.dk/

Project Members

Christian Wiwie

(Former group member)

Publications

(Wiwie et al., 2017) (Wiwie et al., 2019) (Wiwie et al., 2019)
  1. Christian Wiwie, Alexander Rauch, Anders Haakonsson, Inigo Barrio-Hernandez, Blagoy Blagoev, Susanne Mandrup, Richard Röttger and Jan Baumbach. Elucidation of time-dependent systems biology cell response patterns with time course network enrichment. arXiv preprint arXiv:1710.10262 (2017). Link. An extended version of the manuscript is now published in Systems Medicine.
  2. Christian Wiwie, Irina Kuznetsova, Ahmed Mostafa, Alexander Rauch, Anders Haakonsson, Inigo Barrio-Hernandez, Blagoy Blagoev, Susanne Mandrup, Harald HHW Schmidt, Stephan Pleschka, Richard Röttger and Jan Baumbach. Time-Resolved Systems Medicine Reveals Viral Infection-Modulating Host Targets. Systems Medicine 2(1): 1–9 (2019). Link.
  3. Christian Wiwie, Richard Röttger and Jan Baumbach. TiCoNE 2: A Composite Clustering Model for Robust Cluster Analyses on Noisy Data. arXiv preprint arXiv:1904.12353 (2019). Link.

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