Analysis and Design of Frequency-Based Biological Signaling Cascades
Naeini, A. E.; Nejad, S.; O'Donnell, D.; Kuhlman, T. E.
Show abstract
Based on our experimental observation of activation state oscillations of different frequencies used to communicate information by the master human stress response regulator protein p38 MAPK 1, we develop a simple graphical approach for understanding and predicting the behavior of complex biological networks acting upon signals carrying information as different frequency waves of chemicals. This approach uses the same techniques used for analyzing and understanding information transmission using waves of electrical currents and fields used in electrical alternating current (AC) circuits. We show how biological components can be organized to behave as standard components found in electronic telecommunications circuits. Finally, we demonstrate how such components can be organized into complex biological signaling cascades whose behavior can be qualitatively and quantitatively understood, and whose output resembles that experimentally observed in p38.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A biologically plausible decision-making model based on interacting cortical columns 94%
- Coherent feedback leads to robust background compensation in oscillatory and non-oscillatory homeostats 93%
- Probabilistic associative learning suffices for learning the temporal structure of multiple sequences 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.