Using ILP to Identify Pathway Activation Patterns in Systems Biology

Sam Neaves; Louise Millard; Sophia Tsoka

doi:10.1007/978-3-319-40566-7_10

Using ILP to Identify Pathway Activation Patterns in Systems Biology

Sam Neaves, Louise Millard, Sophia Tsoka

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

2 Citations (Scopus)

322 Downloads (Pure)

Abstract

We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist.

Original language	English
Title of host publication	Inductive Logic Programming
Subtitle of host publication	25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers
Editors	Katsumi Inoue, Hayato Ohwada, Akihiro Yamamoto
Publisher	Springer Verlag
Pages	137-151
Number of pages	15
ISBN (Electronic)	9783319405667
ISBN (Print)	9783319405650
DOIs	https://doi.org/10.1007/978-3-319-40566-7_10
Publication status	Published - 10 Jun 2016

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	9575
ISSN (Print)	0302-9743

Keywords

Biological pathways
Warmr
TreeLiker
Reactome
Barcode
Logical aggregation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-40566-7_10

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Springer at http://link.springer.com/chapter/10.1007%2F978-3-319-40566-7_10. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 657 KB

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IEU Theme 2
Flach, P. A. (Principal Investigator), Gaunt, T. R. (Principal Investigator) & Gaunt, T. R. (Principal Investigator)
1/06/13 → 31/03/18
Project: Research

Cite this

Neaves, S., Millard, L., & Tsoka, S. (2016). Using ILP to Identify Pathway Activation Patterns in Systems Biology. In K. Inoue, H. Ohwada, & A. Yamamoto (Eds.), Inductive Logic Programming: 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers (pp. 137-151). (Lecture Notes in Computer Science; Vol. 9575). Springer Verlag. https://doi.org/10.1007/978-3-319-40566-7_10

Neaves, Sam ; Millard, Louise ; Tsoka, Sophia. / Using ILP to Identify Pathway Activation Patterns in Systems Biology. Inductive Logic Programming: 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers. editor / Katsumi Inoue ; Hayato Ohwada ; Akihiro Yamamoto. Springer Verlag, 2016. pp. 137-151 (Lecture Notes in Computer Science).

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abstract = "We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist.",

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Neaves, S, Millard, L & Tsoka, S 2016, Using ILP to Identify Pathway Activation Patterns in Systems Biology. in K Inoue, H Ohwada & A Yamamoto (eds), Inductive Logic Programming: 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers. Lecture Notes in Computer Science, vol. 9575, Springer Verlag, pp. 137-151. https://doi.org/10.1007/978-3-319-40566-7_10

Using ILP to Identify Pathway Activation Patterns in Systems Biology. / Neaves, Sam; Millard, Louise; Tsoka, Sophia.
Inductive Logic Programming: 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers. ed. / Katsumi Inoue; Hayato Ohwada; Akihiro Yamamoto. Springer Verlag, 2016. p. 137-151 (Lecture Notes in Computer Science; Vol. 9575).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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N2 - We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist.

AB - We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist.

KW - Biological pathways

KW - Warmr

KW - TreeLiker

KW - Reactome

KW - Barcode

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DO - 10.1007/978-3-319-40566-7_10

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Neaves S, Millard L, Tsoka S. Using ILP to Identify Pathway Activation Patterns in Systems Biology. In Inoue K, Ohwada H, Yamamoto A, editors, Inductive Logic Programming: 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers. Springer Verlag. 2016. p. 137-151. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-40566-7_10

Using ILP to Identify Pathway Activation Patterns in Systems Biology

Abstract

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Keywords

UN SDGs

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Projects

IEU Theme 2

Cite this