Information-theoretic biodescriptors for proteomics maps: Applications to rodent hepatotoxicity

Subhash C. Basak, Brian D. Gute, Kevin T. Geiss, Frank Witzmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper describes an approach using information theory to derive a complexity measure for proteomics maps generated using 2-dimensional gel electrophoresis (2DE gel). The maps used in this study were partitioned into 5×5 grids and total protein abundance in each grid square was compared to the total abundance for the entire map. Next, Shannon's relation was applied to characterize the distribution of protein abundance across the entire map. Details of the approach are discussed, including an example of the calculations for one proteomics map containing 200 spots. Finally, results for the Map Information Content index are presented for a set of six maps calculated using 200, 500, and 1,400 protein spots. It is hoped that the application of information-theoretic techniques to characterize the complexity of these maps, thus reducing the amount of information presented to the researcher, will help in comparing maps containing a great deal of information and yield information useful in computational toxicology.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Pages10-13
Number of pages4
Volume963
Edition2
DOIs
StatePublished - 2007
EventInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007 - Corfu, Greece
Duration: Sep 25 2007Sep 30 2007

Other

OtherInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007
CountryGreece
CityCorfu
Period9/25/079/30/07

Fingerprint

rodents
proteins
grids
toxicology
information theory
electrophoresis
gels

Keywords

  • 2DE gel
  • Biodescriptor
  • Complexity
  • Halocarbon
  • Hepatotoxicity
  • Information theory
  • Map information content
  • Proteomics
  • Proteomics maps

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Basak, S. C., Gute, B. D., Geiss, K. T., & Witzmann, F. (2007). Information-theoretic biodescriptors for proteomics maps: Applications to rodent hepatotoxicity. In AIP Conference Proceedings (2 ed., Vol. 963, pp. 10-13) https://doi.org/10.1063/1.2835935

Information-theoretic biodescriptors for proteomics maps : Applications to rodent hepatotoxicity. / Basak, Subhash C.; Gute, Brian D.; Geiss, Kevin T.; Witzmann, Frank.

AIP Conference Proceedings. Vol. 963 2. ed. 2007. p. 10-13.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Basak, SC, Gute, BD, Geiss, KT & Witzmann, F 2007, Information-theoretic biodescriptors for proteomics maps: Applications to rodent hepatotoxicity. in AIP Conference Proceedings. 2 edn, vol. 963, pp. 10-13, International Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007, Corfu, Greece, 9/25/07. https://doi.org/10.1063/1.2835935
Basak, Subhash C. ; Gute, Brian D. ; Geiss, Kevin T. ; Witzmann, Frank. / Information-theoretic biodescriptors for proteomics maps : Applications to rodent hepatotoxicity. AIP Conference Proceedings. Vol. 963 2. ed. 2007. pp. 10-13
@inproceedings{e6fb7ba5cb884cbba9f5f5f3d8979fc9,
title = "Information-theoretic biodescriptors for proteomics maps: Applications to rodent hepatotoxicity",
abstract = "This paper describes an approach using information theory to derive a complexity measure for proteomics maps generated using 2-dimensional gel electrophoresis (2DE gel). The maps used in this study were partitioned into 5×5 grids and total protein abundance in each grid square was compared to the total abundance for the entire map. Next, Shannon's relation was applied to characterize the distribution of protein abundance across the entire map. Details of the approach are discussed, including an example of the calculations for one proteomics map containing 200 spots. Finally, results for the Map Information Content index are presented for a set of six maps calculated using 200, 500, and 1,400 protein spots. It is hoped that the application of information-theoretic techniques to characterize the complexity of these maps, thus reducing the amount of information presented to the researcher, will help in comparing maps containing a great deal of information and yield information useful in computational toxicology.",
keywords = "2DE gel, Biodescriptor, Complexity, Halocarbon, Hepatotoxicity, Information theory, Map information content, Proteomics, Proteomics maps",
author = "Basak, {Subhash C.} and Gute, {Brian D.} and Geiss, {Kevin T.} and Frank Witzmann",
year = "2007",
doi = "10.1063/1.2835935",
language = "English",
isbn = "9780735404786",
volume = "963",
pages = "10--13",
booktitle = "AIP Conference Proceedings",
edition = "2",

}

TY - GEN

T1 - Information-theoretic biodescriptors for proteomics maps

T2 - Applications to rodent hepatotoxicity

AU - Basak, Subhash C.

AU - Gute, Brian D.

AU - Geiss, Kevin T.

AU - Witzmann, Frank

PY - 2007

Y1 - 2007

N2 - This paper describes an approach using information theory to derive a complexity measure for proteomics maps generated using 2-dimensional gel electrophoresis (2DE gel). The maps used in this study were partitioned into 5×5 grids and total protein abundance in each grid square was compared to the total abundance for the entire map. Next, Shannon's relation was applied to characterize the distribution of protein abundance across the entire map. Details of the approach are discussed, including an example of the calculations for one proteomics map containing 200 spots. Finally, results for the Map Information Content index are presented for a set of six maps calculated using 200, 500, and 1,400 protein spots. It is hoped that the application of information-theoretic techniques to characterize the complexity of these maps, thus reducing the amount of information presented to the researcher, will help in comparing maps containing a great deal of information and yield information useful in computational toxicology.

AB - This paper describes an approach using information theory to derive a complexity measure for proteomics maps generated using 2-dimensional gel electrophoresis (2DE gel). The maps used in this study were partitioned into 5×5 grids and total protein abundance in each grid square was compared to the total abundance for the entire map. Next, Shannon's relation was applied to characterize the distribution of protein abundance across the entire map. Details of the approach are discussed, including an example of the calculations for one proteomics map containing 200 spots. Finally, results for the Map Information Content index are presented for a set of six maps calculated using 200, 500, and 1,400 protein spots. It is hoped that the application of information-theoretic techniques to characterize the complexity of these maps, thus reducing the amount of information presented to the researcher, will help in comparing maps containing a great deal of information and yield information useful in computational toxicology.

KW - 2DE gel

KW - Biodescriptor

KW - Complexity

KW - Halocarbon

KW - Hepatotoxicity

KW - Information theory

KW - Map information content

KW - Proteomics

KW - Proteomics maps

UR - http://www.scopus.com/inward/record.url?scp=71449098912&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71449098912&partnerID=8YFLogxK

U2 - 10.1063/1.2835935

DO - 10.1063/1.2835935

M3 - Conference contribution

AN - SCOPUS:71449098912

SN - 9780735404786

VL - 963

SP - 10

EP - 13

BT - AIP Conference Proceedings

ER -