A network-based approach for identifying cancer causing pathogens

Joseph Hannigan; Suzanne J. Matthews; John K. Wickiser; Paulo Shakarian

doi:10.1145/2638404.2735459

A network-based approach for identifying cancer causing pathogens

Joseph Hannigan, Suzanne J. Matthews, John K. Wickiser, Paulo Shakarian

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

Abstract

We present a new method to identify malignant cancer-causing pathogens by analyzing their interactions with the host protein interaction network. We introduce two new measurements, core score and moment score that is based on topological characteristics of the network of host proteins that interact with the pathogen. We applied these measurement to a data set consisting of the interactions of 135 pathogens and a human protein-interaction network. We show a strong linear relationship (R2 = 0:90) between the core score and the probability that a pathogen leads to malignant cancer in humans and demonstrate, using a decision tree classifier, that both measurements can be used to correctly identify pathogens that lead to malignant cancer in humans with an accuracy of 97%.

Original language	English (US)
Title of host publication	Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450329231
DOIs	https://doi.org/10.1145/2638404.2735459
State	Published - Mar 28 2014
Externally published	Yes
Event	2014 ACM Southeast Regional Conference, ACM SE 2014 - Kennesaw, United States Duration: Mar 28 2014 → Mar 29 2014

Publication series

Name	Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014

Other

Other	2014 ACM Southeast Regional Conference, ACM SE 2014
Country/Territory	United States
City	Kennesaw
Period	3/28/14 → 3/29/14

Keywords

Cancer
Network topology
Pathogens
Protein interaction networks

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Science Applications
Hardware and Architecture
Software

Access to Document

10.1145/2638404.2735459

Cite this

Hannigan, J., Matthews, S. J., Wickiser, J. K., & Shakarian, P. (2014). A network-based approach for identifying cancer causing pathogens. In Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014 Article 2735459 (Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014). Association for Computing Machinery. https://doi.org/10.1145/2638404.2735459

A network-based approach for identifying cancer causing pathogens. / Hannigan, Joseph; Matthews, Suzanne J.; Wickiser, John K. et al.
Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014. Association for Computing Machinery, 2014. 2735459 (Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014).

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

Hannigan, J, Matthews, SJ, Wickiser, JK & Shakarian, P 2014, A network-based approach for identifying cancer causing pathogens. in Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014., 2735459, Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014, Association for Computing Machinery, 2014 ACM Southeast Regional Conference, ACM SE 2014, Kennesaw, United States, 3/28/14. https://doi.org/10.1145/2638404.2735459

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title = "A network-based approach for identifying cancer causing pathogens",

abstract = "We present a new method to identify malignant cancer-causing pathogens by analyzing their interactions with the host protein interaction network. We introduce two new measurements, core score and moment score that is based on topological characteristics of the network of host proteins that interact with the pathogen. We applied these measurement to a data set consisting of the interactions of 135 pathogens and a human protein-interaction network. We show a strong linear relationship (R2 = 0:90) between the core score and the probability that a pathogen leads to malignant cancer in humans and demonstrate, using a decision tree classifier, that both measurements can be used to correctly identify pathogens that lead to malignant cancer in humans with an accuracy of 97%.",

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author = "Joseph Hannigan and Matthews, {Suzanne J.} and Wickiser, {John K.} and Paulo Shakarian",

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doi = "10.1145/2638404.2735459",

language = "English (US)",

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AU - Hannigan, Joseph

AU - Matthews, Suzanne J.

AU - Wickiser, John K.

AU - Shakarian, Paulo

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N2 - We present a new method to identify malignant cancer-causing pathogens by analyzing their interactions with the host protein interaction network. We introduce two new measurements, core score and moment score that is based on topological characteristics of the network of host proteins that interact with the pathogen. We applied these measurement to a data set consisting of the interactions of 135 pathogens and a human protein-interaction network. We show a strong linear relationship (R2 = 0:90) between the core score and the probability that a pathogen leads to malignant cancer in humans and demonstrate, using a decision tree classifier, that both measurements can be used to correctly identify pathogens that lead to malignant cancer in humans with an accuracy of 97%.

AB - We present a new method to identify malignant cancer-causing pathogens by analyzing their interactions with the host protein interaction network. We introduce two new measurements, core score and moment score that is based on topological characteristics of the network of host proteins that interact with the pathogen. We applied these measurement to a data set consisting of the interactions of 135 pathogens and a human protein-interaction network. We show a strong linear relationship (R2 = 0:90) between the core score and the probability that a pathogen leads to malignant cancer in humans and demonstrate, using a decision tree classifier, that both measurements can be used to correctly identify pathogens that lead to malignant cancer in humans with an accuracy of 97%.

KW - Cancer

KW - Network topology

KW - Pathogens

KW - Protein interaction networks

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M3 - Conference contribution

T3 - Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014

BT - Proceedings of the 2014 ACM Southeast Regional Conference, ACM SE 2014

PB - Association for Computing Machinery

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A network-based approach for identifying cancer causing pathogens

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

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