TY  - GEN
A1  - May, Patrick
A1  - Christian, Jan-Ole
A1  - Kempa, Stefan
A1  - Walther, Dirk
T1  - ChlamyCyc : an integrative systems biology database and web-portal for Chlamydomonas reinhardtii
N2  - Background: The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern highthroughput technologies there is an imperative need to integrate large-scale data sets from highthroughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. Results: In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. Conclusion: ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - paper 127 
KW  - Biochemical pathway database
KW  - Gene-expression data
KW  - Quantitative proteomics
KW  - Metabolic pathways
KW  - Genome annotation
Y1  - 2009
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-44947
ER  - 
TY  - JOUR
A1  - Christian, Jan-Ole
A1  - Braginets, Rostyslav
A1  - Schulze, Waltraud X.
A1  - Walther, Dirk
T1  - Characterization and prediction of protein phosphorylation hotspots in Arabidopsis thaliana
JF  - Frontiers in plant science
N2  - The regulation of protein function by modulating the surface charge status via sequence-locally enriched phosphorylation sites (P-sites) in so called phosphorylation "hotspots" has gained increased attention in recent years. We set out to identify P-hotspots in the model plant Arabidopsis thaliana. We analyzed the spacing of experimentally detected P-sites within peptide-covered regions along Arabidopsis protein sequences as available from the PhosPhAt database. Confirming earlier reports (Schweiger and Lanial, 2010), we found that, indeed, P-sites tend to cluster and that distributions between serine and threonine P-sites to their respected closest next P-site differ significantly from those for tyrosine P-sites. The ability to predict P-hotspots by applying available computational P-site prediction programs that focus on identifying single P-sites was observed to be severely compromised by the inevitable interference of nearby P-sites. We devised a new approach, named HotSPotter, for the prediction of phosphorylation hotspots. HotSPotter is based primarily on local amino acid compositional preferences rather than sequence position-specific motifs and uses support vector machines as the underlying classification engine. HotSPotter correctly identified experimentally determined phosphorylation hotspots in A. thaliana with high accuracy. Applied to the Arabidopsis proteome, HotSPotter-predicted 13,677 candidate P-hotspots in 9,599 proteins corresponding to 7,847 unique genes. Hotspot containing proteins are involved predominantly in signaling processes confirming the surmised modulating role of hotspots in signaling and interaction events. Our study provides new bioinformatics means to identify phosphorylation hotspots and lays the basis for further investigating novel candidate P-hotspots. All phosphorylation hotspot annotations and predictions have been made available as part of the PhosPhAt database at http://phosphat.mpimp-golm.mpg.de.
KW  - protein phosphorylation
KW  - hotspots
KW  - Arabidopsis thaliana
KW  - support vector machines
KW  - regulation
Y1  - 2012
U6  - https://doi.org/10.3389/fpls.2012.00207
SN  - 1664-462X
VL  - 3
PB  - Frontiers Research Foundation
CY  - Lausanne
ER  -