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Inverse modeling of diffusion-reaction processes with image-type measurement data. / Penenko, Alexey; Mukatova, Zhadyra.

11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 39-43 8544885.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Penenko, A & Mukatova, Z 2018, Inverse modeling of diffusion-reaction processes with image-type measurement data. in 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings., 8544885, Institute of Electrical and Electronics Engineers Inc., pp. 39-43, 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018, Novosibirsk, Russian Federation, 20.08.2018. https://doi.org/10.1109/CSGB.2018.8544885

APA

Penenko, A., & Mukatova, Z. (2018). Inverse modeling of diffusion-reaction processes with image-type measurement data. In 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings (pp. 39-43). [8544885] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSGB.2018.8544885

Vancouver

Penenko A, Mukatova Z. Inverse modeling of diffusion-reaction processes with image-type measurement data. In 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 39-43. 8544885 doi: 10.1109/CSGB.2018.8544885

Author

Penenko, Alexey ; Mukatova, Zhadyra. / Inverse modeling of diffusion-reaction processes with image-type measurement data. 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 39-43

BibTeX

@inproceedings{0078f67588b344cf9a0ea890fc8278aa,
title = "Inverse modeling of diffusion-reaction processes with image-type measurement data",
abstract = "The inverse source problem for 1D diffusion-reaction model is considered. The measurement data is given as the images of the concentration fields dynamics for the subset of the interacting species. These inverse problems arise in the study of the growing tissues (morphogenes theory), in the development of the tissue engineering technologies and in the other fields of modern mathematical biology. The sensitivity operator, composed of the ensemble of the independent adjoint problem solutions allow to transform the inverse problem to the family of nonlinear ill-posed integral equations. Each member of the family correspond to the image to structure operator that extracts certain features of the image. An equation from the family is solved with the Newton-Kantorovich-type algorithm combining truncated SVD and iterative regularization. Due to the design with the adjoint problems ensemble, the algorithm can be efficiently parallelized. The algorithm's convergence and stability are illustrated numerically in Brusselator model case.",
keywords = "adjoint problems ensemble, diffusion-reaction, image data, inverse problem, iterative regularization, Newton-Kantorovich method, sensitivity operator, truncated SVD",
author = "Alexey Penenko and Zhadyra Mukatova",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 ; Conference date: 20-08-2018 Through 25-08-2018",
year = "2018",
month = nov,
day = "26",
doi = "10.1109/CSGB.2018.8544885",
language = "English",
pages = "39--43",
booktitle = "11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - Inverse modeling of diffusion-reaction processes with image-type measurement data

AU - Penenko, Alexey

AU - Mukatova, Zhadyra

N1 - Publisher Copyright: © 2018 IEEE.

PY - 2018/11/26

Y1 - 2018/11/26

N2 - The inverse source problem for 1D diffusion-reaction model is considered. The measurement data is given as the images of the concentration fields dynamics for the subset of the interacting species. These inverse problems arise in the study of the growing tissues (morphogenes theory), in the development of the tissue engineering technologies and in the other fields of modern mathematical biology. The sensitivity operator, composed of the ensemble of the independent adjoint problem solutions allow to transform the inverse problem to the family of nonlinear ill-posed integral equations. Each member of the family correspond to the image to structure operator that extracts certain features of the image. An equation from the family is solved with the Newton-Kantorovich-type algorithm combining truncated SVD and iterative regularization. Due to the design with the adjoint problems ensemble, the algorithm can be efficiently parallelized. The algorithm's convergence and stability are illustrated numerically in Brusselator model case.

AB - The inverse source problem for 1D diffusion-reaction model is considered. The measurement data is given as the images of the concentration fields dynamics for the subset of the interacting species. These inverse problems arise in the study of the growing tissues (morphogenes theory), in the development of the tissue engineering technologies and in the other fields of modern mathematical biology. The sensitivity operator, composed of the ensemble of the independent adjoint problem solutions allow to transform the inverse problem to the family of nonlinear ill-posed integral equations. Each member of the family correspond to the image to structure operator that extracts certain features of the image. An equation from the family is solved with the Newton-Kantorovich-type algorithm combining truncated SVD and iterative regularization. Due to the design with the adjoint problems ensemble, the algorithm can be efficiently parallelized. The algorithm's convergence and stability are illustrated numerically in Brusselator model case.

KW - adjoint problems ensemble

KW - diffusion-reaction

KW - image data

KW - inverse problem

KW - iterative regularization

KW - Newton-Kantorovich method

KW - sensitivity operator

KW - truncated SVD

UR - http://www.scopus.com/inward/record.url?scp=85059743521&partnerID=8YFLogxK

U2 - 10.1109/CSGB.2018.8544885

DO - 10.1109/CSGB.2018.8544885

M3 - Conference contribution

AN - SCOPUS:85059743521

SP - 39

EP - 43

BT - 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Conference Bioinformatics of Genome Regulation and Structure\Systems Biology, BGRS\SB 2018

Y2 - 20 August 2018 through 25 August 2018

ER -

ID: 18119050