2010 ExtractingTemporalSignaturesfor

• (Sundaravaradan et al., 2010) ⇒ Naren Sundaravaradan, K.S.M. Tozammel Hossain, Vandana Sreedharan, Douglas J. Slotta, John Paul C. Vergara, Lenwood S. Heath, and Naren Ramakrishnan. (2010). “Extracting Temporal Signatures for Comprehending Systems Biology Models.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835863

Subject Headings:

Notes

• Categories and Subject Descriptors: G.3 Probability and Statistics: Time series analysis; I.5.2 Design Methodology: Feature evaluation and selection; H.2.8 Database Applications: Data mining.
• General Terms: Algorithms, Measurement, Experimentation

Cited By

• http://scholar.google.com/scholar?q=%22Extracting+temporal+signatures+for+comprehending+systems+biology+models%22+2010
• http://portal.acm.org/citation.cfm?id=1835863&preflayout=flat#citedby

Quotes

Author Keywords

Temporal signatures, systems biology, feature selection, rank-order spaces, biological networks.

Abstract

Systems biology has made massive strides in recent years, with capabilities to model complex systems including cell division, stress response, energy metabolism, and signaling pathways. Concomitant with their improved modeling capabilities, however, such biochemical network models have also become notoriously complex for humans to comprehend. We propose network comprehension as a key problem for the KDD community, where the goal is to create explainable representations of complex biological networks. We formulate this problem as one of extracting temporal signatures from multivariate time series data, where the signatures are composed of ordinal comparisons between time series components. We show how such signatures can be inferred by formulating the data mining problem as one of feature selection in rank-order space. We propose five new feature selection strategies for rank-order space and assess their selective superiorities. Experimental results on budding yeast cell cycle models demonstrate compelling results comparable to human interpretations of the cell cycle.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 ExtractingTemporalSignaturesfor	Naren Ramakrishnan Naren Sundaravaradan K.S.M. Tozammel Hossain Vandana Sreedharan Douglas J. Slotta John Paul C. Vergara Lenwood S. Heath			Extracting Temporal Signatures for Comprehending Systems Biology Models		KDD-2010 Proceedings		10.1145/1835804.1835863		2010