Publications

Conferences:

  1. Barker, T. S., Thomas, P. J., & Pierobon, M. (2023, December). A Metric to Quantify Subjective Information in Biological Gradient Sensing. In GLOBECOM 2023-2023 IEEE Global Communications Conference (pp. 577-582). IEEE. [PDF]
  2. Gorla, K. R., & Pierobon, M. (2023, September). Frequency Analysis of a Redox-Based Molecular-Electrical Communication Channel. In Proceedings of the 10th ACM International Conference on Nanoscale Computing and Communication (pp. 21-26). [PDF]
  3. Ratti, F., Harper, C., Magarini, M., & Pierobon, M. (2021, December). Optimizing information transfer through chemical channels in molecular communication. In 2021 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6). IEEE. [PDF]
  4. Gorla, K. R., & Pierobon, M. (2021, September). A mutual information estimate for a redox-based molecular-electrical communication channel. In Proceedings of the Eight Annual ACM International Conference on Nanoscale Computing and Communication (pp. 1-2). [PDF]
  5. Barker, T., Thomas, P. J., & Pierobon, M. (2021, September). Subjective Information in Life Processes: A Computational Case Study. In Proceedings of the Eight Annual ACM International Conference on Nanoscale Computing and Communication (pp. 1-6). [PDF]

 

Complete list of conference publications

 

 

Journals:

  1. Gorla, K. R., Kim, E., Payne, G. F., & Pierobon, M. (2024). Modeling and Characterization of a Molecular-to-Electrical Communication Channel Enabled by Redox Reactions. IEEE Journal on Selected Areas in Communications. [PDF]
  2. Catlett, J. L., Carr, S., Cashman, M., Smith, M. D., Walter, M., Sakkaff, Z., ... & Buan, N. R. (2022). Metabolic synergy between human symbionts Bacteroides and Methanobrevibacter. Microbiology spectrum, 10(3), e01067-22. [PDF]
  3. Barker, T. S., Pierobon, M., & Thomas, P. J. (2022). Subjective information and survival in a simulated biological system. Entropy, 24(5), 639. [PDF]
  4. Dogan, H., Hakguder, Z., Madadjim, R., Scott, S., Pierobon, M., & Cui, J. (2021). Elucidation of dynamic microRNA regulations in cancer progression using integrative machine learning. Briefings in bioinformatics, 22(6), bbab270. [PDF]
  5. Barros, M. T., Veletić, M., Kanada, M., Pierobon, M., Vainio, S., Balasingham, I., & Balasubramaniam, S. (2021). Molecular communications in viral infections research: Modeling, experimental data, and future directions. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 7(3), 121-141. [PDF]

 

Complete list of journal publications

 

 

Others:

  1. Sakkaff, Z., Freiburger, A. P., Catlett, J. L., Cashman, M., Immaneni, A., Buan, N. R., ... & Pierobon, M. (2023). A Molecular Communication model for cellular metabolism. bioRxiv, 2023-06. [PDF]
  2. Balasubramaniam, S., Somathilaka, S., Sun, S., Ratwatte, A., & Pierobon, M. (2023). Realizing molecular machine learning through communications for biological ai. IEEE nanotechnology magazine, 17(3), 10-20. [PDF]
  3. Sakkaff, Z., Freiburger, A., Gupta, N., Pierobon, M., & Henry, C. S. (2023). Information-and Communication-Centric Approach in Cell Metabolism for Analyzing Behavior of Microbial Communities. bioRxiv, 2023-08. [PDF]
  4. Balasubramaniam, S., Schober, R., Pierobon, M., Misra, S., & Thomas, P. (2022). Guest Editorial Special Issue on “Edge-Based Wireless Communications Technologies to Counter Communicable Infectious Diseases”. IEEE Journal on Selected Areas in Communications, 40(11), 3119-3121. [PDF]
  5. Balasubramaniam, S., Barros, M. T., Veletić, M., Kanada, M., Pierobon, M., Vainio, S., & Balasingham, I. (2021). Special Issue on Molecular Communications for Diagnostics and Therapeutic Development of Infectious Diseases. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 7(3), 117-120. [PDF]

 

Complete list of other publications