TY - JOUR
T1 - Resources and tools for investigating biomolecular networks in mammals
AU - Dietmann, Sabine
AU - Aguilar, Daniel
AU - Mader, Michael
AU - Oesterheld, Matthias
AU - Ruepp, Andreas
AU - Stuempflen, Volker
AU - Mewes, Hans Werner
PY - 2006/10
Y1 - 2006/10
N2 - Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.
AB - Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.
KW - Clustering algorithms
KW - Function annotation
KW - Functional modules
KW - Microarray data
KW - Ontologies
KW - Protein interaction networks
UR - http://www.scopus.com/inward/record.url?scp=33749824909&partnerID=8YFLogxK
U2 - 10.2174/138161206778559722
DO - 10.2174/138161206778559722
M3 - Review article
C2 - 17073671
AN - SCOPUS:33749824909
SN - 1381-6128
VL - 12
SP - 3723
EP - 3734
JO - Current Pharmaceutical Design
JF - Current Pharmaceutical Design
IS - 29
ER -