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Institution

Center for Integrated Protein Science Munich

OtherMunich, Germany
About: Center for Integrated Protein Science Munich is a other organization based out in Munich, Germany. It is known for research contribution in the topics: Chromatin & Ribosome. The organization has 1140 authors who have published 1241 publications receiving 65075 citations.
Topics: Chromatin, Ribosome, RNA, Protein structure, Histone


Papers
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Journal ArticleDOI
TL;DR: An open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM–based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.lmu.de/hhblits/).
Abstract: Sequence-based protein function and structure prediction depends crucially on sequence-search sensitivity and accuracy of the resulting sequence alignments. We present an open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM-based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.lmu.de/hhblits/). Compared to the sequence-search tool PSI-BLAST, HHblits is faster owing to its discretized-profile prefilter, has 50-100% higher sensitivity and generates more accurate alignments.

1,865 citations

Journal ArticleDOI
29 May 2014-Nature
TL;DR: A mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB are presented, which enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.
Abstract: Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs). Analysis of messenger RNA and protein-expression profiles of human tissues revealed conserved control of protein abundance, and integration of drug-sensitivity data enabled the identification of proteins predicting resistance or sensitivity. The proteome profiles also hold considerable promise for analysing the composition and stoichiometry of protein complexes. ProteomicsDB thus enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.

1,660 citations

Journal ArticleDOI
TL;DR: Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB- sequencing, and Smart-seq2 are more efficient when analyzing fewer cells.

1,041 citations

Journal ArticleDOI
TL;DR: A computational tool for predicting the structure of DNA Origami objects is introduced and information is provided on the conditions under which DNA origami objects can be expected to maintain their structure.
Abstract: Molecular self-assembly with scaffolded DNA origami enables building custom-shaped nanometer-scale objects with molecular weights in the megadalton regime. Here we provide a practical guide for design and assembly of scaffolded DNA origami objects. We also introduce a computational tool for predicting the structure of DNA origami objects and provide information on the conditions under which DNA origami objects can be expected to maintain their structure.

818 citations

Journal ArticleDOI
23 Dec 2010-PLOS ONE
TL;DR: The data suggest that an active oxidative mC demethylation pathway is unlikely to occur and show that hmC is present in all tissues and cell types with highest concentrations in neuronal cells of the CNS.
Abstract: 5-Hydroxymethylcytosine (hmC) was recently detected as the sixth base in mammalian tissue at so far controversial levels. The function of the modified base is currently unknown, but it is certain that the base is generated from 5-methylcytosine (mC). This fuels the hypothesis that it represents an intermediate of an active demethylation process, which could involve further oxidation of the hydroxymethyl group to a formyl or carboxyl group followed by either deformylation or decarboxylation. Here, we use an ultra-sensitive and accurate isotope based LC-MS method to precisely determine the levels of hmC in various mouse tissues and we searched for 5-formylcytosine (fC), 5-carboxylcytosine (caC), and 5-hydroxymethyluracil (hmU) as putative active demethylation intermediates. Our data suggest that an active oxidative mC demethylation pathway is unlikely to occur. Additionally, we show using HPLC-MS analysis and immunohistochemistry that hmC is present in all tissues and cell types with highest concentrations in neuronal cells of the CNS.

814 citations


Authors

Showing all 1141 results

NameH-indexPapersCitations
Matthias Mann221887230213
Ruedi Aebersold182879141881
Christian Haass11944558107
Wolfgang Baumeister11353244031
Franz Hofmann11347149938
Thomas Bein10967742800
Horst Kessler10187844392
Johannes Buchner9936034381
Nilay Shah99119652788
Magdalena Götz9223728760
Thomas Cremer8828929486
Arthur Konnerth8620626952
F. Ulrich Hartl8519635238
Andrew J. Martin8481936203
Stefan Endres8329831542
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
20223
202147
202096
2019120
2018110