Standard
Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity. /
Vijayakumar, S.; Angione, C.
Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I. ed. / Ignacio Rojas; Francisco Ortuño. Cham: Springer, 2017. p. 220-229 (Lecture Notes in Computer Science; Vol. 10208).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Vijayakumar, S & Angione, C 2017,
Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity. in I Rojas & F Ortuño (eds),
Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I. Lecture Notes in Computer Science, vol. 10208, Springer, Cham, pp. 220-229.
https://doi.org/10.1007/978-3-319-56148-6_19
APA
Vijayakumar, S., & Angione, C. (2017).
Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity. In I. Rojas, & F. Ortuño (Eds.),
Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I (pp. 220-229). (Lecture Notes in Computer Science; Vol. 10208). Springer.
https://doi.org/10.1007/978-3-319-56148-6_19
Vancouver
Vijayakumar S, Angione C.
Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity. In Rojas I, Ortuño F, editors, Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I. Cham: Springer. 2017. p. 220-229. (Lecture Notes in Computer Science). Epub 2017 Apr 1. doi: 10.1007/978-3-319-56148-6_19
Author
Vijayakumar, S. ; Angione, C. /
Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity. Bioinformatics and Biomedical Engineering: 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part I. editor / Ignacio Rojas ; Francisco Ortuño. Cham : Springer, 2017. pp. 220-229 (Lecture Notes in Computer Science).
Bibtex
@inproceedings{e0903cee5a8b4036a172195e6f7323be,
title = "Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity",
abstract = "Synechococcus sp. PCC 7002 is a fast-growing cyanobacterium which flourishes in freshwater and marine environments, owing to its ability to tolerate high light intensity and a wide range of salinities. Harnessing the properties of cyanobacteria and understanding their metabolic efficiency has become an imperative goal in recent years owing to their potential to serve as biocatalysts for the production of renewable biofuels. To improve characterisation of metabolic networks, genome-scale models of metabolism can be integrated with multi-omic data to provide a more accurate representation of metabolic capability and refine phenotypic predictions. In this work, a heuristic pipeline is constructed for analysing a genome-scale metabolic model of Synechococcus sp. PCC 7002, which utilises flux balance analysis across multiple layers to observe flux response between conditions across four key pathways. Across various conditions, the detection of significant patterns and mechanisms to cope with fluctuations in light intensity and salinity provides insights into the maintenance of metabolic efficiency.",
keywords = "Multi-omics, Synechococcus, Stress conditions, Adaptation, Light and salinity, Phototrophic growth",
author = "S. Vijayakumar and C. Angione",
year = "2017",
month = apr,
day = "26",
doi = "10.1007/978-3-319-56148-6_19",
language = "English",
isbn = "9783319561479",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "220--229",
editor = "Ignacio Rojas and Francisco Ortu{\~n}o",
booktitle = "Bioinformatics and Biomedical Engineering",
}
RIS
TY - GEN
T1 - Multi-omic data integration elucidates Synechococcus adaptation mechanisms to fluctuations in light intensity and salinity
AU - Vijayakumar, S.
AU - Angione, C.
PY - 2017/4/26
Y1 - 2017/4/26
N2 - Synechococcus sp. PCC 7002 is a fast-growing cyanobacterium which flourishes in freshwater and marine environments, owing to its ability to tolerate high light intensity and a wide range of salinities. Harnessing the properties of cyanobacteria and understanding their metabolic efficiency has become an imperative goal in recent years owing to their potential to serve as biocatalysts for the production of renewable biofuels. To improve characterisation of metabolic networks, genome-scale models of metabolism can be integrated with multi-omic data to provide a more accurate representation of metabolic capability and refine phenotypic predictions. In this work, a heuristic pipeline is constructed for analysing a genome-scale metabolic model of Synechococcus sp. PCC 7002, which utilises flux balance analysis across multiple layers to observe flux response between conditions across four key pathways. Across various conditions, the detection of significant patterns and mechanisms to cope with fluctuations in light intensity and salinity provides insights into the maintenance of metabolic efficiency.
AB - Synechococcus sp. PCC 7002 is a fast-growing cyanobacterium which flourishes in freshwater and marine environments, owing to its ability to tolerate high light intensity and a wide range of salinities. Harnessing the properties of cyanobacteria and understanding their metabolic efficiency has become an imperative goal in recent years owing to their potential to serve as biocatalysts for the production of renewable biofuels. To improve characterisation of metabolic networks, genome-scale models of metabolism can be integrated with multi-omic data to provide a more accurate representation of metabolic capability and refine phenotypic predictions. In this work, a heuristic pipeline is constructed for analysing a genome-scale metabolic model of Synechococcus sp. PCC 7002, which utilises flux balance analysis across multiple layers to observe flux response between conditions across four key pathways. Across various conditions, the detection of significant patterns and mechanisms to cope with fluctuations in light intensity and salinity provides insights into the maintenance of metabolic efficiency.
KW - Multi-omics
KW - Synechococcus
KW - Stress conditions
KW - Adaptation
KW - Light and salinity
KW - Phototrophic growth
U2 - 10.1007/978-3-319-56148-6_19
DO - 10.1007/978-3-319-56148-6_19
M3 - Conference contribution/Paper
SN - 9783319561479
T3 - Lecture Notes in Computer Science
SP - 220
EP - 229
BT - Bioinformatics and Biomedical Engineering
A2 - Rojas, Ignacio
A2 - Ortuño, Francisco
PB - Springer
CY - Cham
ER -
