Network Component Analysis (NCA)
Introduction
NCA is a data decomposition technique, which
relies on
certain a-priori knowledge on the network topology in order to
reconstruct both
the network input signals as well as the strength of its connections,
when only
the output signals are accessible. BioSpice’s NCA is a Matlab package
at whose
core is a routine for the analysis and parameter estimation of
transcriptional
regulatory networks. NCA requires two separate types of inputs. The
first is a
description of the available connectivity information between genes and
transcriptional factors (obtained for example as the result of binding
site
analysis), which is given as a boolean adjacency matrix. The second is
a set of
gene expression level time-courses, of the type obtainable for example
by DNA
microarray experiments.
Related
Articles
J.C. Liao, R. Boscolo,Y.-L. Yang, L.M. Tran, C. Sabatti, and V.P.
Roychowdhury (2003). “Network-enabled reconstruction of regulatory
signals in biological systems”. Proceedings
of the National Academy of Sciences (PNAS), 100(26):15522–15527. [pdf]
K.C. Kao, Young-Lyeol Yang, Riccardo Boscolo, Chiara Sabatti, Vwani
Roychowdhury, and James C. Liao (2004). “Determination of multiple
transcription regulator activities in Escherichia coli using network
component analysis”. Proceedings of
the National Academy of Sciences (PNAS),101(2):641–646. [pdf]
R. Boscolo, C. Sabatti, J.C. Liao, and Vwani P. Roychowdhury (2004).
"Reconstructing Hidden Regulatory Layers by Network Component Analysis:
Theory and Application", submitted to IEEE
Trans. on Computational Biology and Bioinformatics. [ps] [pdf]
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Last
updated on August 09 2004 by Riccardo Boscolo