Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data

Jana Schwarzerová; Dominika Olešová; Aleš Kvasnička; David Friedecký; Margaret Varga; Valentine Provazník; Wolfram Weckwerth

doi:10.1007/978-3-031-34953-9_30

Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data

Jana Schwarzerová (Corresponding author)
, Dominika Olešová (Corresponding author)
, Aleš Kvasnička
, David Friedecký
, Margaret Varga
, Valentine Provazník
, Wolfram Weckwerth

Functional and Evolutionary Ecology

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

Abstract

Comprehensive analysis of lipids is becoming a forefront of clinical data analysis. Due to significant technical advancements, lipidomics is emerging in clinical diagnostics for improvement and earlier detection of a broad range of diseases. However, in order to understand the biological complexities and interrelationships between the molecules, it is important to have a correct representation of the data and visualizations that enable good interpretability of the lipidomic data. Therefore, the present study systematically compares different visualization methods for lipidomic data, based on different computational relations between the selected lipids and supplemented with known biological information. Networks were reconstructed, and an analysis was performed to objectively compare the visualizations.

Original language	English
Title of host publication	Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings
Editors	Ignacio Rojas, Olga Valenzuela, Fernando Rojas Ruiz, Luis Javier Herrera, Francisco Ortuño
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	378-389
Number of pages	12
ISBN (Print)	9783031349522
DOIs	https://doi.org/10.1007/978-3-031-34953-9_30
Publication status	Published - 23 Jun 2023
Event	10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023 - Meloneras, Spain Duration: 12 Jul 2023 → 14 Jul 2023

Publication series

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13919 LNBI
ISSN	0302-9743

Conference

Conference	10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023
Country/Territory	Spain
City	Meloneras
Period	12/07/23 → 14/07/23

Funding

Acknowledgements. Computational resources were supplied by the Ministry of Education, Youth and Sports of the Czech Republic under the Projects CESNET (Project No. LM2015042) and CERIT-Scientific Cloud (Project No. LM2015085) provided within the program Projects of Large Research, Development and Innovations Infrastructures.

Austrian Fields of Science 2012

301302 Lipidomics research
106005 Bioinformatics

Keywords

Comprehensive Analysis
Lipids
Network Visualization
Networks Analysis

Access to Document

10.1007/978-3-031-34953-9_30

Cite this

Schwarzerová, J., Olešová, D., Kvasnička, A., Friedecký, D., Varga, M., Provazník, V., & Weckwerth, W. (2023). Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data. In I. Rojas, O. Valenzuela, F. Rojas Ruiz, L. J. Herrera, & F. Ortuño (Eds.), Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings (pp. 378-389). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-34953-9_30

Schwarzerová, Jana ; Olešová, Dominika ; Kvasnička, Aleš et al. / Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data. Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings. editor / Ignacio Rojas ; Olga Valenzuela ; Fernando Rojas Ruiz ; Luis Javier Herrera ; Francisco Ortuño. Springer Science and Business Media Deutschland GmbH, 2023. pp. 378-389 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13919 LNBI).

@inproceedings{37887f7da92640b9802ad2f00a910c93,

title = "Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data",

abstract = "Comprehensive analysis of lipids is becoming a forefront of clinical data analysis. Due to significant technical advancements, lipidomics is emerging in clinical diagnostics for improvement and earlier detection of a broad range of diseases. However, in order to understand the biological complexities and interrelationships between the molecules, it is important to have a correct representation of the data and visualizations that enable good interpretability of the lipidomic data. Therefore, the present study systematically compares different visualization methods for lipidomic data, based on different computational relations between the selected lipids and supplemented with known biological information. Networks were reconstructed, and an analysis was performed to objectively compare the visualizations.",

keywords = "Comprehensive Analysis, Lipids, Network Visualization, Networks Analysis",

author = "Jana Schwarzerov{\'a} and Dominika Ole{\v s}ov{\'a} and Ale{\v s} Kvasni{\v c}ka and David Friedeck{\'y} and Margaret Varga and Valentine Provazn{\'i}k and Wolfram Weckwerth",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Computational resources were supplied by the Ministry of Education, Youth and Sports of the Czech Republic under the Projects CESNET (Project No. LM2015042) and CERIT-Scientific Cloud (Project No. LM2015085) provided within the program Projects of Large Research, Development and Innovations Infrastructures.; 10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023 ; Conference date: 12-07-2023 Through 14-07-2023",

year = "2023",

month = jun,

day = "23",

doi = "10.1007/978-3-031-34953-9\_30",

language = "English",

isbn = "9783031349522",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "378--389",

editor = "Ignacio Rojas and Olga Valenzuela and \{Rojas Ruiz\}, Fernando and Herrera, \{Luis Javier\} and Francisco Ortu{\~n}o",

booktitle = "Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings",

}

Schwarzerová, J, Olešová, D, Kvasnička, A, Friedecký, D, Varga, M, Provazník, V & Weckwerth, W 2023, Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data. in I Rojas, O Valenzuela, F Rojas Ruiz, LJ Herrera & F Ortuño (eds), Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings. Springer Science and Business Media Deutschland GmbH, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13919 LNBI, pp. 378-389, 10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023, Meloneras, Spain, 12/07/23. https://doi.org/10.1007/978-3-031-34953-9_30

Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data. / Schwarzerová, Jana (Corresponding author); Olešová, Dominika (Corresponding author); Kvasnička, Aleš et al.
Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings. ed. / Ignacio Rojas; Olga Valenzuela; Fernando Rojas Ruiz; Luis Javier Herrera; Francisco Ortuño. Springer Science and Business Media Deutschland GmbH, 2023. p. 378-389 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13919 LNBI).

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

TY - GEN

T1 - Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data

AU - Schwarzerová, Jana

AU - Olešová, Dominika

AU - Kvasnička, Aleš

AU - Friedecký, David

AU - Varga, Margaret

AU - Provazník, Valentine

AU - Weckwerth, Wolfram

N1 - Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Computational resources were supplied by the Ministry of Education, Youth and Sports of the Czech Republic under the Projects CESNET (Project No. LM2015042) and CERIT-Scientific Cloud (Project No. LM2015085) provided within the program Projects of Large Research, Development and Innovations Infrastructures.

PY - 2023/6/23

Y1 - 2023/6/23

N2 - Comprehensive analysis of lipids is becoming a forefront of clinical data analysis. Due to significant technical advancements, lipidomics is emerging in clinical diagnostics for improvement and earlier detection of a broad range of diseases. However, in order to understand the biological complexities and interrelationships between the molecules, it is important to have a correct representation of the data and visualizations that enable good interpretability of the lipidomic data. Therefore, the present study systematically compares different visualization methods for lipidomic data, based on different computational relations between the selected lipids and supplemented with known biological information. Networks were reconstructed, and an analysis was performed to objectively compare the visualizations.

AB - Comprehensive analysis of lipids is becoming a forefront of clinical data analysis. Due to significant technical advancements, lipidomics is emerging in clinical diagnostics for improvement and earlier detection of a broad range of diseases. However, in order to understand the biological complexities and interrelationships between the molecules, it is important to have a correct representation of the data and visualizations that enable good interpretability of the lipidomic data. Therefore, the present study systematically compares different visualization methods for lipidomic data, based on different computational relations between the selected lipids and supplemented with known biological information. Networks were reconstructed, and an analysis was performed to objectively compare the visualizations.

KW - Comprehensive Analysis

KW - Lipids

KW - Network Visualization

KW - Networks Analysis

UR - https://www.scopus.com/pages/publications/85164957599

U2 - 10.1007/978-3-031-34953-9_30

DO - 10.1007/978-3-031-34953-9_30

M3 - Contribution to proceedings

AN - SCOPUS:85164957599

SN - 9783031349522

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 378

EP - 389

BT - Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings

A2 - Rojas, Ignacio

A2 - Valenzuela, Olga

A2 - Rojas Ruiz, Fernando

A2 - Herrera, Luis Javier

A2 - Ortuño, Francisco

PB - Springer Science and Business Media Deutschland GmbH

T2 - 10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023

Y2 - 12 July 2023 through 14 July 2023

ER -

Schwarzerová J, Olešová D, Kvasnička A, Friedecký D, Varga M, Provazník V et al. Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data. In Rojas I, Valenzuela O, Rojas Ruiz F, Herrera LJ, Ortuño F, editors, Bioinformatics and Biomedical Engineering - 10th International Work-Conference, IWBBIO 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 378-389. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13919 LNBI). doi: 10.1007/978-3-031-34953-9_30

Systematic Comparison of Advanced Network Analysis and Visualization of Lipidomics Data

Abstract

Publication series

Conference

Funding

Austrian Fields of Science 2012

Keywords

Access to Document

Other files and links

Fingerprint

Cite this