From evidence to inference: Probing the evolution of protein interaction networks
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From evidence to inference : Probing the evolution of protein interaction networks. / Ratmann, Oliver; Wiuf, Carsten; Pinney, John W.
I: HFSP Journal, Bind 3, Nr. 5, 01.10.2009, s. 290-306.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - From evidence to inference
T2 - Probing the evolution of protein interaction networks
AU - Ratmann, Oliver
AU - Wiuf, Carsten
AU - Pinney, John W.
PY - 2009/10/1
Y1 - 2009/10/1
N2 - The evolutionary mechanisms by which protein interaction networks grow and change are beginning to be appreciated as a major factor shaping their present-day structures and properties. Starting with a consideration of the biases and errors inherent in our current views of these networks, we discuss the dangers of constructing evolutionary arguments from naïve analyses of network topology. We argue that progress in understanding the processes of network evolution is only possible when hypotheses are formulated as plausible evolutionary models and compared against the observed data within the framework of probabilistic modeling. The value of such models is expected to be greatly enhanced as they incorporate more of the details of the biophysical properties of interacting proteins, gene phylogeny, and measurement error and as more advanced methodologies emerge for model comparison and the inference of ancestral network states.
AB - The evolutionary mechanisms by which protein interaction networks grow and change are beginning to be appreciated as a major factor shaping their present-day structures and properties. Starting with a consideration of the biases and errors inherent in our current views of these networks, we discuss the dangers of constructing evolutionary arguments from naïve analyses of network topology. We argue that progress in understanding the processes of network evolution is only possible when hypotheses are formulated as plausible evolutionary models and compared against the observed data within the framework of probabilistic modeling. The value of such models is expected to be greatly enhanced as they incorporate more of the details of the biophysical properties of interacting proteins, gene phylogeny, and measurement error and as more advanced methodologies emerge for model comparison and the inference of ancestral network states.
UR - http://www.scopus.com/inward/record.url?scp=77649095212&partnerID=8YFLogxK
U2 - 10.2976/1.3167215
DO - 10.2976/1.3167215
M3 - Journal article
AN - SCOPUS:77649095212
VL - 3
SP - 290
EP - 306
JO - HFSP Journal
JF - HFSP Journal
SN - 2155-3769
IS - 5
ER -
ID: 203905946