Efficient algorithms for detecting signaling pathways in protein interaction networks

Efficient algorithms for detecting signaling pathways in protein interaction networks (2005)

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by Jacob Scott , Trey Ideker , Richard M. Karp , Roded Sharan

Venue:	Journal of Computational Biology
Citations:	47 - 2 self

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@ARTICLE{Scott05efficientalgorithms,
    author = {Jacob Scott and Trey Ideker and Richard M. Karp and Roded Sharan},
    title = {Efficient algorithms for detecting signaling pathways in protein interaction networks},
    journal = {Journal of Computational Biology},
    year = {2005},
    volume = {13},
    pages = {2006}
}

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Abstract

Abstract. The interpretation of large-scale protein network data depends on our ability to identify significant sub-structures in the data, a computationally intensive task. Here we adapt and extend efficient techniques for finding paths in graphs to the problem of identifying pathways in protein interaction networks. We present linear-time algorithms for finding paths in networks under several biologically-motivated constraints. We apply our methodology to search for protein pathways in the yeast protein-protein interaction network. We demonstrate that our algorithm is capable of reconstructing known signaling pathways and identifying functionally enriched paths in an unsupervised manner. The algorithm is very efficient, computing optimal paths of length 8 within minutes and paths of length 10 in less than two hours. 1

Citations

261	P: Comparative assessment of large-scale data sets of protein-protein interactions - Mering, Krause, et al.
165	DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions - Xenarios, Salwinski, et al. - 2002
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56	Gaining confidence in high-throughput protein interaction networks - Bader, Chaudhuri, et al. - 2004
53	Assessing experimentally derived interactions in a small world - S, Roth - 2003
49	T: Assessment of the reliability of proteinprotein interactions and protein function prediction - Deng, Sun, et al.
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29	Wholegenome annotation by using evidence integration in functional-linkage networks - Karaoz, Murali, et al.
26	Automated modelling of signal transduction networks - Steffen, Petti, et al.
22	et al., “Comparative assessment of large-scale data sets of protein-protein interactions - Mering, Krause, et al. - 2002
15	et al., “MIPS: analysis and annotation of proteins from whole genomes - Mewes, Amid, et al. - 2004
12	et al. Conserved pathways within bacteria and yeast as revealed by global protein network alignment - Kelley, Sharan, et al. - 2004
9	et al, “DIP: The Database of Interacting Proteins. A research tool for studying cellular networks of protein interactions.” NAR - Xenarios, Salwinski, et al.
3	et al. Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles - Roberts
2	et al., “The Stanford Microarray Database: Data Access and Quality Assessment Tools - Gollub - 2003
1	et al.: Assessing experimentally derived interactions in a small world - Goldberg - 2003