Accession Number:

ADA622227

Title:

Solving Inverse Problems for Mechanistic Systems Biology Models with Unknown Inputs

Descriptive Note:

Final rept. 1 Jan-30 Sep 2014

Corporate Author:

MARYLAND UNIV COLLEGE PARK

Personal Author(s):

Report Date:

2014-10-16

Pagination or Media Count:

31.0

Abstract:

The goal of the proposed project is to develop and test the feasibility of a novel approach to solve the inverse problem for a class of systems arising from systems biology study, in which input is unknown e.g. cannot be observed but multiple outputs can be observed. As mentioned above, the most significant challenge associated with this class of inverse problems is that the standard approach to inverse problem where the parameters of the mechanistic model are optimized to fit the input-output data is not applicable in the absence of system input observation. To resolve this challenge, this project proposes to exploit the commonality shared by the outputs that originate from the same input. Indeed, noting that these outputs originate from the identical input, a relationship between these outputs can be formulated, which can subsequently be utilized in solving the inverse problem without necessitating the input observations.

Subject Categories:

  • Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE