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Leukemia Research, August 2008
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Ligand-induced Flt3-downregulation modulates cell death associated proteins and enhances chemosensitivity to idarubicin in THP-1 acute myeloid leukemia cells |
Eystein Oveland, Bjørn Tore Gjertsen, Line Wergeland, Frode Selheim, Kari E. Fladmark, Randi Hovland
Analytical Chemistry, April 2008
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Performance of Combinatorial Peptide Libraries in Capturing the Low-Abundance Proteome of Red Blood Cells. 1. Behavior of Mono- to Hexapeptides. |
Simó C, Bachi A, Cattaneo A, Guerrier L, Fortis F., Boschetti E, Podtelejnikov A, and Righetti PG.
Journal of Proteome Research, January 2008
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A Proteome Resource of Ovarian Cancer Ascites: Integrated Proteomic and Bioinformatic Analyses To Identify Putative Biomarkers |
" Comparison of our ascites proteome resource to the HUPO plasma proteome data (3020 proteins and a recently published urine proteome data set (1543 proteins) was performed using ProteinCenter" Limor Gortzak-Uzan 1,2,', Alex Ignatchenko 1,', Andreas I. Evangelou 1,', Mahima Agochiya 3, Kevin A. Brown 3, Peter St.Onge 5 Inga Kireeva 1, Gerold Schmitt-Ulms6, Theodore J. Brown 4,7, Joan Murphy 2,7, Barry Rosen 2,7, Patricia Shaw 6, Igor Jurisica 1,8,9 and Thomas Kislinger 1,8,* ' Authors contributed equally to this work. 1 Ontario Cancer Institute, Division of Cancer Genomics and Proteomics. 2 Division of Gynecological Oncology, Princess Margaret Hospital. 3 Ontario Cancer Institute, Division of Signaling Biology. 4 Samuel Lunenfeld Research Institute. 5 Department of Cell and Systems Biology, University of Toronto. 6 Department of Laboratory Medicine and Pathology, University of Toronto. 7 Department of Obstetrics and Gynecology, University of Toronto. 8 Department of Medical Biophysics, University of Toronto. 9 Department of Computer Science, University of Toronto.
Journal of Proteome Research, December 2007
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Integrated Analysis of the Cerebrospinal Fluid Peptidome and Proteome |
"Due to support of major protein sequence databases and computational enrichment, ProteinCenter decreases the redundancy of the databases and significantly improves protein annotation." Alexandre Zougman1, Bartosz Pilch,1, 2, Alexandre Podtelejnikov 3, Michael Kiehntopf 4, Claudia Schnabel 5, Chanchal Kumar 1 and Matthias Mann 1
1 Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry Am Klopferspitz 18, 82152 Martinsried, Germany 2 Center for Experimental BioInformatics (CEBI), Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark 3 Proxeon Bioinformatics A/S, Staermosegaardsvej 6, DK-5230, Denmark 4 Institute of Clinical Chemistry and Laboratory Medecine, University of Jena, Germany 5 Department of Clinical Chemistry, Center for Clinical Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
Molecular & Cellular Proteomics, November 2007
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SILAC-labeling and proteome quantitation of mouse embryonic stem cells to a depth of 5111 proteins |
"We used ProteinCenter to compare the results of the two prefractionation methods subcellular fractionation in combination with SDS-gel electrophoresis and isoelectric focusing." Johannes Graumann1,4, Nina C. Hubner1,4, Jeong Beom Kim2, Kinarm Ko2, Markus Moser3 Chanchal Kumar1, Jürgen Cox1, Hans Schöler2 and Matthias Mann1 1 Department of Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Am Klopferspitz, D-82152 Martinsried, Germany 2 Department of Cell and Development Biology, Max-Planck-Institute for Molecular Biomedicine, Roentgenstr. 20, 48149 Münster, Germany 3 Department of Molecular Medicine, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany 4 These authors contributed equally
International Orthopaedics (SICOT), In press, October 2007
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Detection of bone and cartilage-related proteins in plasma of patients with a bone fracture using liquid chromatography-mass spectrometry |
"Gene ontology (GO) analysis was performed using ProteinCenter software package" L. Grgurevici1, B. Macek2, D. Durdevic3,, S. Vukicevic1 1 Labpratory of Mineralized Tissues, School of Medicine, University of Zagreb, Salata 11, 10000 Zagreb, Croatia 2 Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany 3 Cline of Traumatology, Draskoviceva 19, Zagreb, Croatia
Journal of Proteome Research, July 2007
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Analysis of the Mouse Liver Proteome Using Advanced Mass Spectrometry |
"ProteinCenter was used to compare experimental data sets with previously published HUPO plasma data sets. The similarity threshold of 70 % was chosen as the cutoff to define clusters of sequences. The liver proteins belonging to the clusters of at least two proteins with at least one identifier from the HUPO data set were deemed overlapping." R. Shi1, C. Kumar1, A. Zougman1, Y. Zhang1,2, A. Podtelejnikov3, J. Cox1, J.R. Wisniewski1, M. Mann1. 1 Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany 2 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 101300, China 3 Proxeon Biosystems A/S, Stærmosegårdsvej 6, 5230 Odense, Denmark
Molecular & Cellular Proteomics, April 2007
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In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics |
"Adipocyte proteome comparison with previous human cell line and drosphila lipid droplet proteomics studies. We used ProteinCenter (Proxeon, Denmark), which is proteomic data mining and management software, to compare our datasets with previously published datasets of 6 human cell lines, and drosophila lipid droplet proteome. Briefly for mapping our dataset to any other dataset we loaded the datasets as two groups in ProteinCenter. The datasets were then clustered based on the sequence similarity, and the optimization criterion used was "most homogeneous groups" wherein protein sequences are clustered to make the individual groups as homogeneous as possible." Jun Adachi 1,3, Chanchal Kumar 1, Yanling Zhang 1,2 and Matthias Mann 1 1 Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry Am Klopferspitz 18, 82152 Martinsried, Germany 2 Beijing Institute of Genomics, Chinese Academy of Sciences Beijing 101300, China 3 Graduate School of Global Environmental Studies, Kyoto University Yoshida-Honmachi Sakyo-Ku, Kyoto 606-8501, Japan
MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes
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MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
"Depending on the project, datasets are joined and checked for overlap using ProteinCenter, a proteomics software suite developed by Proxeon. ProteinCenter also allows us to directly distinguish which isoforms of a protein are present in a proteome, provided that distinguishing peptide sequences have been detected." Yanling Zhang 1,2, Yong Zhang 1,2, Jun Adachi 1,3, Jesper V. Olsen 1, Rong Shi 1, Gustavo de Souza 1, Erica Pasini 4, Leonard J. Foster 5, Boris Macek 1, Alexandre Zougman 1, Chanchal Kumar 1, Jacek R. Winiewski 1, Wang Jun 2,6 and Matthias Mann 1 1 Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry Am Klopferspitz 18, 82152 Martinsried, Germany 2 Beijing Institute of Genomics, Chinese Academy of Sciences Beijing 101300, China 3 Graduate School of Global Environmental Studi, Kyoto University Yoshida- Honmachi Sakyo-Ku, Kyoto 606-8501, Japan 4 Biomedical Primate Research Centre, Lange Kleiweg 139 2288 GJ Rijswijk, The Netherlands 5 Department of Biochemistry and Molecular Biology, Centre for Proteomics, University of British Columbia Vancouver, BC V6T 1Z4, USA 6 Department of Biochemistry and Molecular Biology, University of Southern Denmark DK-5230 Odense M, Denmark
Genome Biology, Volume 7, 2006
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Large-scale and high-confidence proteomic analysis of human seminal Plasma |
"To prepare a final list of proteins, we used ProteinCenter, a program to analyze the results of proteomic experiments bioinformatically. In particular, ProteinCenter assigns peptide identifications to proteins, resolving ambiguities resulting from peptides matching different members of protein families. Information about which protein was identified in which sample is also kept. ProteinCenter also curates the identified proteome for signal peptides, transmembrane regions, and alternative splicing, and allows analysis of biological function and cellular roles. Results of ProteinCenter analysis, including the occurrence of proteins in one, two, or three samples and bioinformatic annotation, can be found in Additional data file 1." "A comparison between our data and previously described proteomes using ProteinCenter is presented." "The merging of data was performed with ProteinCenter, which collapses entries with at least 98% sequence homology and groups homologous sequences." Bartosz Pilch 1,2 and Matthias Mann 1,2 1 Center for Experimental BioInformatics (CEBI), Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, DK- 5230 Odense M, Denmark 2 Department of Proteomics and Signal Transduction, Max Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
Genome Biology, Volume 7, 2006
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The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins |
"In order to compare the different protein identifiers, protein IDs in each dataset were converted to gene symbols using ProteinCenter." "For counting the number of identified proteins across each experiment, redundant protein identification was removed using Blast search function of ProteinCenter and manual check." Jun Adachi 1,2,3, Chanchal Kumar 1, Yanling Zhang 1,4, Jesper V Olsen 1,2 and Matthias Mann 1,2 1 Department of Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Am Klopferspitz, D-82152 Martinsried, Germany 2 Center for Experimental Bioinformatics, University of Southern Denmark, Campusvej, DK-5230 Odense M, Denmark 3 Current address: Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi Sakyo-Ku, Kyoto, Japan 4 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 101300, China
Genome Biology, Volume 7, 2006
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Identification of 491 proteins in the tear fluid proteome reveals a large number of proteases and protease inhibitors |
"The 491 proteins identified in the in-gel analysis were functionally classified using the ProteinCenter Tool" "Identified proteins were combined in a larger data set and initial GO characterization was done using the ProteinCenter tool" Gustavo A de Souza 1,2, Lyris MF Godoy 1,2 and Matthias Mann 1,2 1 Center for Experimental BioInformatics (CEBI), Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej, DK-5230 Odense M, Denmark 2 Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz, D-82152 Martinsried, Germany
Cell, November 2006
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Global, In Vivo, and Site-Specific Phosphorylation Dynamics in Signaling Networks |
"Alexandre Podtelejnikov and Søren Gade of Proxeon A/S are acknowledged for their help with bioinformatic analysis using ProteinCenter." Jesper V. Olsen 1,2,3, Blagoy Blagoev 1,3, Florian Gnad 2,3, Boris Macek 1,2, Chanchal Kumar 2, Peter Mortensen 1 and Matthias Mann 1,2 1 Center for Experimental BioInformatics, Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense, Denmark 2 Department of Proteomics and Signal Transduction, Max-Planck-Institute for Biochemistry, D-82152 Martinsried, Germany
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