Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

Suresh Bhavnani, Arunkumaar Ganesan, Theodore Hall, Eric Maslowski, Felix Eichinger, Sebastian Martini, Paul Saxman, Gowtham Bellala, Matthias Kretzler

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Background: In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings: The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions: The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks.

Original languageEnglish
Article number296
JournalBMC Research Notes
Volume3
DOIs
StatePublished - 2010

Fingerprint

Visualization
Genes
Kidney
Gene expression
Chronic Renal Insufficiency

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations. / Bhavnani, Suresh; Ganesan, Arunkumaar; Hall, Theodore; Maslowski, Eric; Eichinger, Felix; Martini, Sebastian; Saxman, Paul; Bellala, Gowtham; Kretzler, Matthias.

In: BMC Research Notes, Vol. 3, 296, 2010.

Research output: Contribution to journalArticle

Bhavnani, S, Ganesan, A, Hall, T, Maslowski, E, Eichinger, F, Martini, S, Saxman, P, Bellala, G & Kretzler, M 2010, 'Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations', BMC Research Notes, vol. 3, 296. https://doi.org/10.1186/1756-0500-3-296
Bhavnani, Suresh ; Ganesan, Arunkumaar ; Hall, Theodore ; Maslowski, Eric ; Eichinger, Felix ; Martini, Sebastian ; Saxman, Paul ; Bellala, Gowtham ; Kretzler, Matthias. / Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations. In: BMC Research Notes. 2010 ; Vol. 3.
@article{0dc89492083a4f49933e75543910a655,
title = "Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations",
abstract = "Background: In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings: The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions: The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks.",
author = "Suresh Bhavnani and Arunkumaar Ganesan and Theodore Hall and Eric Maslowski and Felix Eichinger and Sebastian Martini and Paul Saxman and Gowtham Bellala and Matthias Kretzler",
year = "2010",
doi = "10.1186/1756-0500-3-296",
language = "English",
volume = "3",
journal = "BMC Research Notes",
issn = "1756-0500",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

AU - Bhavnani, Suresh

AU - Ganesan, Arunkumaar

AU - Hall, Theodore

AU - Maslowski, Eric

AU - Eichinger, Felix

AU - Martini, Sebastian

AU - Saxman, Paul

AU - Bellala, Gowtham

AU - Kretzler, Matthias

PY - 2010

Y1 - 2010

N2 - Background: In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings: The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions: The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks.

AB - Background: In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings: The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions: The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks.

UR - http://www.scopus.com/inward/record.url?scp=78149309723&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78149309723&partnerID=8YFLogxK

U2 - 10.1186/1756-0500-3-296

DO - 10.1186/1756-0500-3-296

M3 - Article

VL - 3

JO - BMC Research Notes

JF - BMC Research Notes

SN - 1756-0500

M1 - 296

ER -