Identification of gene network motifs for cancer disease diagnosis

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

1 Citation (Scopus)

Abstract

All networks, including biological networks, computer networks, social networks and more can be represented as graphs, which include a number of small module such as subgraph, also called as network motifs. Network motifs are subgraph which recur themselves in a specific network or different networks. In biological networks, these network motifs plays very important role to identify diseases in human beings. In this paper we have developed a module to identify common network motifs types from cancer pathways and Signal Transduction Networks (STNs). It also identifies t he t opological behaviors o f cancer networks and STNs. In this study, we have implemented five motif algorithms such as Auto-Regulation Loop (ARL), Feed Backward Loop (FBL), Feed Forward Loop (FFL), Single-Input Motif (SIM) and Bi-fan. These algorithms gives correct results in terms of network motifs for human cancer and STNs. Finding network motifs by using online tool is limited to three nodes, but our proposed work provides facility to find network motifs upto any number of nodes. We applied five motif algorithms to human cancer networks and Signal Transduction Networks (STNs) which are collected from KEGG database as a result we got 'Frequent Occurrences of Network Motifs (FONMs)'. These FONMs acts as a references for an oncologist in order to find type o f cancer in human beings.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages179-184
Number of pages6
ISBN (Electronic)9781509016235
DOIs
Publication statusPublished - 01-01-2016
Event2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Mangalore, India
Duration: 13-08-201614-08-2016

Conference

Conference2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016
CountryIndia
CityMangalore
Period13-08-1614-08-16

Fingerprint

Signal transduction
Genes
Computer networks
Fans

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Gupta, R., Fayaz, S. M., & Singh, S. (2016). Identification of gene network motifs for cancer disease diagnosis. In 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings (pp. 179-184). [7806253] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DISCOVER.2016.7806253
Gupta, Rohit ; Fayaz, S. M. ; Singh, Sanjay. / Identification of gene network motifs for cancer disease diagnosis. 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 179-184
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Gupta, R, Fayaz, SM & Singh, S 2016, Identification of gene network motifs for cancer disease diagnosis. in 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings., 7806253, Institute of Electrical and Electronics Engineers Inc., pp. 179-184, 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016, Mangalore, India, 13-08-16. https://doi.org/10.1109/DISCOVER.2016.7806253

Identification of gene network motifs for cancer disease diagnosis. / Gupta, Rohit; Fayaz, S. M.; Singh, Sanjay.

2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 179-184 7806253.

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

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Gupta R, Fayaz SM, Singh S. Identification of gene network motifs for cancer disease diagnosis. In 2016 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 179-184. 7806253 https://doi.org/10.1109/DISCOVER.2016.7806253