Multilayer Networks for Biology

Multilayer network centrality to uncover molecular mediators of tissue-tissue communication.

Biological systems are naturally multilayer, with interactions spanning tissues and molecular scales. This work develops multilayer network centrality measures and studies the effect of inter-layer coupling, applying them to uncover molecular mediators of tissue-tissue communication (MultiCens) and to predict cross-tissue hormone-gene relations via balanced word embeddings.

Representative publications (Kumar et al., 2023; Kumar et al., 2019; Jadhav et al., 2022).

References

2023

  1. PLOS Comp. Bio.
    MultiCens: Multilayer Network Centrality Measures to Uncover Molecular Mediators of Tissue-Tissue Communication
    Tarun Kumar, Ramanathan Sethuraman, Sanga Mitra, and 2 more authors
    PLOS Computational Biology, 2023

2022

  1. Bioinformatics
    Predicting Cross-tissue Hormone-Gene Relations using Balanced Word Embeddings
    Aditya Jadhav, Tarun Kumar, Mohit Raghavendra, and 2 more authors
    Bioinformatics, 2022

2019

  1. J. Indian Inst. Sci.
    Effect of Inter-layer Coupling on Multilayer Network Centrality Measures
    Tarun Kumar, Manikandan Narayanan, and Balaraman Ravindran
    Journal of the Indian Institute of Science, 2019