Learning Relevant Time Points for Time-Series Data in the Life Sciences

Schleif F-M, Mokbel B, Gisbrecht A, Theunissen L, Dürr V, Hammer B (2012)
In: ICANN (2). Lecture Notes in Computer Science, 7553. 531-539.

Conference Paper | Published | English

No fulltext has been uploaded

Abstract
In the life sciences, short time series with high dimensional entries are becoming more and more popular such as spectrometric data or gene expression profiles taken over time. Data characteristics rule out classical time series analysis due to the few time points, and they prevent a simple vectorial treatment due to the high dimensionality. In this contribution, we successfully use the generative topographic mapping through time (GTM-TT) which is based on hidden Markov models enhanced with a topographic mapping to model such data. We propose an extension of GTM-TT by relevance learning which automatically adapts the model such that the most relevant input variables and time points are emphasized by means of an automatic relevance weighting scheme. We demonstrate the technique in two applications from the life sciences.
Publishing Year
PUB-ID

Cite this

Schleif F-M, Mokbel B, Gisbrecht A, Theunissen L, Dürr V, Hammer B. Learning Relevant Time Points for Time-Series Data in the Life Sciences. In: ICANN (2). Lecture Notes in Computer Science. Vol 7553. 2012: 531-539.
Schleif, F. - M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., & Hammer, B. (2012). Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2), 7553, 531-539.
Schleif, F. - M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., and Hammer, B. (2012). “Learning Relevant Time Points for Time-Series Data in the Life Sciences” in ICANN (2) Lecture Notes in Computer Science, vol. 7553, 531-539.
Schleif, F.-M., et al., 2012. Learning Relevant Time Points for Time-Series Data in the Life Sciences. In ICANN (2). Lecture Notes in Computer Science. no.7553 pp. 531-539.
F.-M. Schleif, et al., “Learning Relevant Time Points for Time-Series Data in the Life Sciences”, ICANN (2), Lecture Notes in Computer Science, vol. 7553, 2012, pp.531-539.
Schleif, F.-M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., Hammer, B.: Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2). Lecture Notes in Computer Science. 7553, p. 531-539. (2012).
Schleif, Frank-Michael, Mokbel, Bassam, Gisbrecht, Andrej, Theunissen, Leslie, Dürr, Volker, and Hammer, Barbara. “Learning Relevant Time Points for Time-Series Data in the Life Sciences”. ICANN (2). 2012.Vol. 7553. Lecture Notes in Computer Science. 531-539.
This data publication is cited in the following publications:
This publication cites the following data publications:

Export

0 Marked Publications

Open Data PUB

Search this title in

Google Scholar
ISBN Search