NDLI: Extracting Dynamics from Static Cancer Expression Data

Content Provider	IEEE Xplore Digital Library
Author	Gupta, A. Bar-Joseph, Z.
Copyright Year	2004
Abstract	Static expression experiments analyze samples from many individuals. These samples are often snapshots of the progression of a certain disease such as cancer. This raises an intriguing question: Can we determine a temporal order for these samples? Such an ordering can lead to better understanding of the dynamics of the disease and to the identification of genes associated with its progression. In this paper, we formally prove, for the first time, that under a model for the dynamics of the expression levels of a single gene, it is indeed possible to recover the correct ordering of the static expression data sets by solving an instance of the traveling salesman problem (TSP). In addition, we devise an algorithm that combines a TSP heuristic and probabilistic modeling for inferring the underlying temporal order of the microarray experiments. This algorithm constructs probabilistic continuous curves to represent expression profiles and can thus account for noise and for individual background expression differences leading to accurate temporal reconstruction for human data. Applying our method to cancer expression data, we show that the ordering derived agrees well with survival duration. A classifier that utilizes this ordering improves upon other classifiers suggested for this task. The set of genes displaying consistent behavior for the determined ordering is enriched for genes associated with cancer progression.
Sponsorship	IEEE Computer Society
Page Count	11
File Size	739227
Starting Page	172
Ending Page	182
File Format	PDF
ISSN	15455963
Volume Number	5
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Cancer Diseases Traveling salesman problems Time measurement Background noise Humans Neoplasms Information analysis Animals glioma microarrays traveling salesman EM
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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