TY - CHAP
T1 - Large-scale statistical inference of gene regulatory networks
T2 - Local network-based measures
AU - Emmert-Streib, Frank
PY - 2011
Y1 - 2011
N2 - In this chapter we discuss various local network-based measures in order to assess the performance of inference algorithms for estimating regulatory networks. These statistical measures represent domain specific knowledge and are for this reason better adapted to problems that are directly involving networks compared to other measures frequently used in this context like the F-score. We are discussing three such measures with special focus on the inference of regulatory networks from expression data. However, due to the fact that currently there is a vast interest in network-based approaches in systems biology the presented measures may be also of interest for the analysis of a different type of large-scale genomics data.
AB - In this chapter we discuss various local network-based measures in order to assess the performance of inference algorithms for estimating regulatory networks. These statistical measures represent domain specific knowledge and are for this reason better adapted to problems that are directly involving networks compared to other measures frequently used in this context like the F-score. We are discussing three such measures with special focus on the inference of regulatory networks from expression data. However, due to the fact that currently there is a vast interest in network-based approaches in systems biology the presented measures may be also of interest for the analysis of a different type of large-scale genomics data.
UR - http://www.scopus.com/inward/record.url?scp=84885466009&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-19621-8_8
DO - 10.1007/978-3-642-19621-8_8
M3 - Chapter
AN - SCOPUS:84885466009
SN - 9783642196201
VL - 11
T3 - Intelligent Systems Reference Library
SP - 179
EP - 193
BT - Intelligent Systems Reference Library
ER -