Institution
Braunschweig University of Technology
Education•Braunschweig, Germany•
About: Braunschweig University of Technology is a education organization based out in Braunschweig, Germany. It is known for research contribution in the topics: Population & Computer science. The organization has 13268 authors who have published 26707 publications receiving 611590 citations.
Papers published on a yearly basis
Papers
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TL;DR: To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated, and the information flow that provides the data on the rapid time scale needed for mission success is described.
Abstract: The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University’s Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored on board so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.
977 citations
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TL;DR: A novel method for the adaptation of target gene codon usage to most sequenced prokaryotes and selected eukaryotic gene expression hosts was developed to improve heterologous protein production using JCat (Java Codon Adaptation Tool).
Abstract: A novel method for the adaptation of target gene codon usage to most sequenced prokaryotes and selected eukaryotic gene expression hosts was developed to improve heterologous protein production. In contrast to existing tools, JCat (Java Codon Adaptation Tool) does not require the manual definition of highly expressed genes and is, therefore, a very rapid and easy method. Further options of JCat for codon adaptation include the avoidance of unwanted cleavage sites for restriction enzymes and Rho-independent transcription terminators. The output of JCat is both graphically and as Codon Adaptation Index (CAI) values given for the pasted sequence and the newly adapted sequence. Additionally, a list of genes in FASTA-format can be uploaded to calculate CAI values. In one example, all genes of the genome of Caenorhabditis elegans were adapted to Escherichia coli codon usage and further optimized to avoid commonly used restriction sites. In a second example, the Pseudomonas aeruginosa exbD gene codon usage was adapted to E.coli codon usage with parallel avoidance of the same restriction sites. For both, the degree of introduced changes was documented and evaluated. JCat is integrated into the PRODORIC database that hosts all required information on the various organisms to fulfill the requested calculations. JCat is freely accessible at http://www.prodoric.de/JCat.
970 citations
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University of New South Wales1, Oregon State University2, Braunschweig University of Technology3, University of California, San Diego4, Norwegian University of Life Sciences5, University of Liverpool6, Max Planck Society7, University of Tasmania8, University of Vermont9, ETH Zurich10, Stazione Zoologica Anton Dohrn11, Montana State University12, University of Amsterdam13, University of Southern California14, Pacific Northwest National Laboratory15, University of Hawaii at Manoa16, University of California, Berkeley17, Marine Biological Laboratory18, University of California, Irvine19, University of Georgia20, California Institute of Technology21, University of Edinburgh22, Ohio State University23, University of Sydney24, University of Alberta25, Georgia Institute of Technology26, University of Melbourne27, Australian Institute of Marine Science28, University of Texas Medical Branch29, University of Queensland30
TL;DR: This Consensus Statement documents the central role and global importance of microorganisms in climate change biology and puts humanity on notice that the impact of climate change will depend heavily on responses of micro organisms, which are essential for achieving an environmentally sustainable future.
Abstract: In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial 'unseen majority'. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future.
963 citations
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TL;DR: A systematic overview of the state of the art in energy and resource efficiency increasing methods and techniques in the domain of discrete part manufacturing, with attention for the effectiveness of the available options is provided in this paper.
Abstract: A B S T R A C T This paper aims to provide a systematic overview of the state of the art in energy and resource efficiency increasing methods and techniques in the domain of discrete part manufacturing, with attention for the effectiveness of the available options. For this purpose a structured approach, distinguishing different system scale levels, is applied: starting from a unit process focus, respectively the multi-machine, factory, multi-facility and supply chain levels are covered. Determined by the research contributions reported in literature, the de facto focus of the paper is mainly on energy related aspects of manufacturing. Significant opportunities for systematic efficiency improving measures are identified and summarized in this area. 2012 CIRP.
936 citations
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TL;DR: In a comparison to five well‐established model quality assessment programs, QMEAN shows a statistically significant improvement over nearly all quality measures describing the ability of the scoring function to identify the native structure and to discriminate good from bad models.
Abstract: In protein structure prediction, a considerable number of alternative models are usually produced from which subsequently the final model has to be selected. Thus, a scoring function for the identification of the best model within an ensemble of alternative models is a key component of most protein structure prediction pipelines. QMEAN, which stands for Qualitative Model Energy ANalysis, is a composite scoring function describing the major geometrical aspects of protein structures. Five different structural descriptors are used. The local geometry is analyzed by a new kind of torsion angle potential over three consecutive amino acids. A secondary structure-specific distance-dependent pairwise residue-level potential is used to assess long-range interactions. A solvation potential describes the burial status of the residues. Two simple terms describing the agreement of predicted and calculated secondary structure and solvent accessibility, respectively, are also included. A variety of different implementations are investigated and several approaches to combine and optimize them are discussed. QMEAN was tested on several standard decoy sets including a molecular dynamics simulation decoy set as well as on a comprehensive data set of totally 22,420 models from server predictions for the 95 targets of CASP7. In a comparison to five well-established model quality assessment programs, QMEAN shows a statistically significant improvement over nearly all quality measures describing the ability of the scoring function to identify the native structure and to discriminate good from bad models. The three-residue torsion angle potential turned out to be very effective in recognizing the native fold.
919 citations
Authors
Showing all 13486 results
Name | H-index | Papers | Citations |
---|---|---|---|
Wolfgang Wagner | 156 | 2342 | 123391 |
Helmut Sies | 133 | 670 | 78319 |
Cristina Riccardi | 129 | 1627 | 91452 |
Klaus-Robert Müller | 129 | 764 | 79391 |
Alex Zunger | 128 | 826 | 78798 |
Rolf Müller | 104 | 905 | 50027 |
Rudolf Valenta | 102 | 748 | 38349 |
Oliver G. Schmidt | 100 | 1083 | 39988 |
Kenneth N. Timmis | 97 | 365 | 34912 |
Thomas Braun | 96 | 744 | 38576 |
Ursula Keller | 92 | 934 | 33229 |
William Martin | 90 | 348 | 34353 |
Bruce T. Tsurutani | 85 | 605 | 30358 |
Michael Wink | 83 | 938 | 32658 |
Yves-Alain Barde | 83 | 168 | 35485 |