Date of Award

August 2020

Document Type


Degree Name

Master of Science (MS)


School of Mathematical and Statistical Sciences

Committee Member

Matthew Macauley

Committee Member

Michael Burr

Committee Member

Svetlana Poznanovikj


The network inference problem is a significant problem in systems biology. In this paper, we will describe an approach to this problem involving computational algebra. Specifically, given an unknown Boolean function, we can create a square-free monomial or pseudomonomial ideal whose primary decomposition encodes the possible sets of variables that the function can depend on, and whether those interactions are activations or inhibitions. We apply this problem to time series data generated from a non-linear ODE, built over unknown feed-forward loops, and subject to gene knockouts.



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