Estimating hidden influences in metabolic and gene regulatory networks

Florian Blöchl; Fabian J. Theis

doi:10.1007/978-3-642-00599-2_49

Estimating hidden influences in metabolic and gene regulatory networks

Florian Blöchl, Fabian J. Theis

Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Begutachtung

3 Zitate (Scopus)

Abstract

We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory networks. In simple processes obeying mass action kinetics, we find the emergence of linear mixture models. More complex situations as well as hidden influences in regulatory systems with sigmoidal input functions however lead to new classes of BSS problems.

Originalsprache	Englisch
Seiten (von - bis)	387-394
Seitenumfang	8
Fachzeitschrift	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Jahrgang	5441
DOIs	https://doi.org/10.1007/978-3-642-00599-2_49
Publikationsstatus	Veröffentlicht - 2009
Extern publiziert	Ja
Veranstaltung	8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009 - Paraty, Brasilien Dauer: 15 März 2009 → 18 März 2009

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10.1007/978-3-642-00599-2_49

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abstract = "We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory networks. In simple processes obeying mass action kinetics, we find the emergence of linear mixture models. More complex situations as well as hidden influences in regulatory systems with sigmoidal input functions however lead to new classes of BSS problems.",

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doi = "10.1007/978-3-642-00599-2_49",

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AU - Theis, Fabian J.

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AB - We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory networks. In simple processes obeying mass action kinetics, we find the emergence of linear mixture models. More complex situations as well as hidden influences in regulatory systems with sigmoidal input functions however lead to new classes of BSS problems.

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DO - 10.1007/978-3-642-00599-2_49

M3 - Conference article

AN - SCOPUS:67149102168

SN - 0302-9743

VL - 5441

SP - 387

EP - 394

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009

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ER -

Estimating hidden influences in metabolic and gene regulatory networks

Abstract

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