Formal Analysis of the Biological Circuits using Higher-order-logic Theorem Proving

TL;DR

This paper introduces a higher-order-logic theorem proving framework to formally analyze biological circuits in synthetic biology, aiming to improve accuracy over traditional methods like simulations and paper proofs.

Contribution

It presents a novel formal verification approach using higher-order-logic theorem proving for genetic circuits modeled by differential equations and transfer functions.

Findings

Successfully modeled genetic circuits using differential equations.

Performed formal transfer function analysis via Laplace transform.

Demonstrated practical analysis on activated and repressed protein expression circuits.

Abstract

Synthetic Biology is an interdisciplinary field that utilizes well-established engineering principles, ranging from electrical, control and computer systems, for analyzing the biological systems, such as biological circuits, enzymes, pathways and controllers. Traditionally, these biological systems, i.e., the genetic circuits are analyzed using paper-and-pencil proofs and computer-based simulations techniques. However, these methods cannot provide accurate results due to their inherent limitations such as human error-proneness, round-off errors and the unverified algorithms present in the core of the tools, providing such analyses. In this paper, we propose to use higher-order-logic theorem proving as a complementary technique for analyzing these systems and thus overcome the above-mentioned issues. In particular, we propose a higher-order-logic theorem proving based framework to formally reason about the genetic circuits used in synthetic biology. The main idea is to, first, model the continuous dynamics of the genetic circuits using differential equations. The next step is to obtain the systems' transfer function from their corresponding block diagram representations. Finally, the transfer function based analysis of these differential equation based models is performed using the Laplace transform. To illustrate the practical utilization of our proposed framework, we formally analyze the genetic circuits of activated and repressed expressions of protein.