267 research outputs found
MeltDB : a software platform for the analysis and integration of metabolomics experiment data
No full textNeuweger H. MeltDB : a software platform for the analysis and integration of metabolomics experiment data. Bielefeld (Germany): Bielefeld University; 2009.The recent advances in metabolomics have created the potential to measure the levels of hundreds of metabolites which are the end products of cellular regulatory processes. The automation of the sample acquisition and subsequent analysis in high throughput instruments that are capable of measuring metabolites is posing a challenge on the necessary systematic storage and computational processing of the experimental datasets. Whereas a multitude of specialized software systems for individual instruments and preprocessing methods exists, there is clearly a need for a free and platform-independent system that allows the standardized and integrated storage and analysis of data obtained from metabolomics experiments. Both support for preprocessing of raw datasets and also means to visualize and integrate the results of higher level statistical analyses within a functional genomics context are required.
To facilitate the systematic storage, analysis and integration of metabolomics experiments, MeltDB was designed, implemented, and applied. MeltDB is a web-based software platform for the analysis and annotation of datasets from metabolomics experiments. The software supports open and standardized file formats (netCDF, mzXML, mzDATA) and facilitates the integration and evaluation of existing preprocessing methods. The system provides researchers with means to consistently describe and store their experimental datasets. Comprehensive analysis and visualization features of metabolomics datasets are offered to the community through a web-based user interface. The newly developed system covers the process from raw data management to the visualization of results in a knowledge-based background and is integrated into the existing software platforms of genomics, proteomics, and transcriptomics at Bielefeld University.
This work demonstrates the functionality of MeltDB by means of several application examples where e.g. the influence of three different carbon sources on the gram-negative bacterium Xanthomonas campestris pv. campestris or the differences between healthy and disease human blood plasma samples are dissected. Novel visualization and analysis methods based on the MeltDB API have been developed and evaluated in the context of the extensible software platform
The REGANOR gene prediction server for prokaryotic genomes and a database of high quality gene predictions for prokaryotes
No full textLinke B, McHardy AC, Neuweger H, Krause L, Meyer F. The REGANOR gene prediction server for prokaryotic genomes and a database of high quality gene predictions for prokaryotes. Applied Bioinformatics. 2006;5(3):193-198
ProSE - "Software as a Service" for Quantitative Proteomics (Poster abstract)
No full textAlbaum S, Neuweger H, Lange S, et al. ProSE - "Software as a Service" for Quantitative Proteomics (Poster abstract). In: HUPO 7th Annual World Congress. 2008
Modelling Interregional Trade of Energy Crops in Eastern Germany
No full textRenewable resources gain in importance in our modern society. The line of reasoning is based on their positive effects on agriculture, the environment and the economy. To support renewable energy from biomass the EU promotes the cultivation of energy crops. A spatial equilibrium model is applied based on the concept of maximizing net welfare, to provide information whether energy crop production competes with food production for land area. The Model of Interregional Trade of Energy Crops (ITEC) refers to Eastern Germany and adjacent areas of Poland. First results show that the regions have enough feedstocks to meet the required demand for food and biofuel production. In many cases both food crops and biofuels are either traded on interregional basis or exported to "Rest of Europe" indicating that there is no competition between food and energy crops. Only green maize for biogas production strongly competes in areas where the crop is required as feed for cattle.Energy crops, spatial equilibrium analysis, interregional trade, International Relations/Trade,
Visualizing post genomics data-sets on customized pathway maps by ProMeTra – aeration-dependent gene expression and metabolism of Corynebacterium glutamicum as an example
No full textNeuweger H, Persicke M, Albaum S, et al. Visualizing post genomics data-sets on customized pathway maps by ProMeTra – aeration-dependent gene expression and metabolism of Corynebacterium glutamicum as an example. BMC Systems Biology. 2009;3(1): 82.Background: The rapid progress of post-genomic analyses, such as transcriptomics, proteomics, and metabolomics has resulted in the generation of large amounts of quantitative data covering and connecting the complete cascade from genotype to phenotype for individual organisms. Various benefits can be achieved when these ''Omics'' data are integrated, such as the identification of unknown gene functions or the elucidation of regulatory networks of whole organisms. In order to be able to obtain deeper insights in the generated datasets, it is of utmost importance to present the data to the researcher in an intuitive, integrated, and knowledge-based environment. Therefore, various visualization paradigms have been established during the last years. The visualization of ''Omics'' data using metabolic pathway maps is intuitive and has been applied in various software tools. It has become obvious that the application of web-based and user driven software tools has great potential and benefits from the use of open and standardized formats for the description of pathways. Results: In order to combine datasets from heterogeneous ''Omics'' sources, we present the web-based ProMeTra system that visualizes and combines datasets from transcriptomics, proteomics, and metabolomics on user defined metabolic pathway maps. Therefore, structured exchange of data with our ''Omics'' applications Emma 2, Qupe and MeltDB is employed. Enriched SVG images or animations are generated and can be obtained via the user friendly web interface. To demonstrate the functionality of ProMeTra, we use quantitative data obtained during a fermentation experiment of the L-lysine producing strain Corynebacterium glutamicum DM1730. During fermentation, oxygen supply was switched off in order to perturb the system and observe its reaction. At six different time points, transcript abundances, intracellular metabolite pools, as well as extracellular glucose, lactate, and L-lysine levels were determined. Conclusion: The interpretation and visualization of the results of this complex experiment was facilitated by the ProMeTra software. Both transcriptome and metabolome data were visualized on a metabolic pathway map. Visual inspection of the combined data confirmed existing knowledge but also delivered novel correlations that are of potential biotechnological importance
Erratum to “Size exclusion chromatography—An improved method to harvest Corynebacterium glutamicum cells for the analysis of cytosolic metabolites” [J. Biotechnol. 154 (2–3) (2011) 171–178]
No full textPersicke M, Plassmeier J, Neuweger H, Rückert C, Pühler A, Kalinowski J. Erratum to “Size exclusion chromatography—An improved method to harvest Corynebacterium glutamicum cells for the analysis of cytosolic metabolites” [J. Biotechnol. 154 (2–3) (2011) 171–178]. Journal of Biotechnology. 2011;155(2):266-267
In-situ study of emerging metallicity and memory effect on ion-beam bombarded strontium titanate surface:
No full textIn this work we present an investigation of the occurrence of conductivity on the surface of SrTiO3 due to argon ion bombardment. We created a model to describe this process and found that the temperature during the ion milling is a crucial factor for the conductivity. Depending on the temperatures we found surface carrier densities ranging from 1.5*10^18 to 2.6*10^20cm^-3 by just analyzing the conductivity behavior.
Clustering of vacancies goes along with temperature and affects the conductivity significantly. Furthermore we found that ion milling is a gentle way create vacancies because the clustering rate is small compared to annealing samples in high vacuum. The amount of clusters at room temperature was measured to be around 3-4 times higher than at -140C.
We found that samples with a conducting surface change their resistance over time at room temperature due to the ongoing process of oxygen vacancy clustering. This effect may be suppressed by decreasing the temperature.
The bistable switching behavior in oxygen deficient SrTiO3 is shown without any additional doping. The vacancy migration is the major mechanism behind this memory effect. Comparing this behavior with annealed samples in high vacuum shows that the therein present amount of vacancy clusters must be much larger and has a negative effect on the bistable switching behavior.M.S.Includes bibliographical references (p. 83-87)by Heiko Gros
Handle with Care : Implementation of the List Experiment and Crosswise Model in a Large-Scale Survey on Academic Misconduct
No full textAcknowledgments We thank the anonymous reviewers as well as Alexander Ehlert, Isabel Raabe, and Justus Rathmann for their concise comments and constructive feedback on our work. Co-authors in alphabetical order. Study Design: Julia Jerke, David Johann, Heiko Rauhut, Kathrin Thomas, Antonia Velicu. Coding and Analysis: Julia Jerke, David Johann, Kathrin Thomas, Antonia Velicu. First draft: Julia Jerke, Heiko Rauhut, Kathrin Thomas, Antonia Velicu. Revisions: David Johann, Kathrin Thomas, Antonia Velicu. Final approval of the paper: Julia Jerke, David Johann, Heiko Rauhut, Kathrin Thomas, Antonia Velicu. Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by the Swiss National Science Foundation (SNSF), Starting Grant “CONCISE” BSSGIO 155981 of Heiko Rauhut.Peer reviewe
Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets
No full textHoffmann N, Keck M, Neuweger H, et al. Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets. BMC Bioinformatics. 2012;13(1): 21.Background
Modern analytical methods in biology and chemistry use separation techniques coupled to sensitive detectors, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). These hyphenated methods provide high-dimensional data. Comparing such data manually to find corresponding signals is a laborious task, as each experiment usually consists of thousands of individual scans, each containing hundreds or even thousands of distinct signals. In order to allow for successful identification of metabolites or proteins within such data, especially in the context of metabolomics and proteomics, an accurate alignment and matching of corresponding features between two or more experiments is required. Such a matching algorithm should capture fluctuations in the chromatographic system which lead to non-linear distortions on the time axis, as well as systematic changes in recorded intensities. Many different algorithms for the retention time alignment of GC-MS and LC-MS data have been proposed and published, but all of them focus either on aligning previously extracted peak features or on aligning and comparing the complete raw data containing all available features.
Results
In this paper we introduce two algorithms for retention time alignment of multiple GC-MS datasets: multiple alignment by bidirectional best hits peak assignment and cluster extension (BIPACE) and center-star multiple alignment by pairwise partitioned dynamic time warping (CEMAPP-DTW). We show how the similarity-based peak group matching method BIPACE may be used for multiple alignment calculation individually and how it can be used as a preprocessing step for the pairwise alignments performed by CEMAPP-DTW. We evaluate the algorithms individually and in combination on a previously published small GC-MS dataset studying the Leishmania parasite and on a larger GC-MS dataset studying grains of wheat (Triticum aestivum).
Conclusions
We have shown that BIPACE achieves very high precision and recall and a very low number of false positive peak assignments on both evaluation datasets. CEMAPP-DTW finds a high number of true positives when executed on its own, but achieves even better results when BIPACE is used to constrain its search space. The source code of both algorithms is included in the OpenSource software framework Maltcms, which is available from http://maltcms.sf.net webcite. The evaluation scripts of the present study are available from the same source
The Definitive Guide to NetBeans Platform
No full textThe Definitive Guide to NetBeans(t) Platform is a thorough and definitive introduction to the NetBeans Platform, covering all its major APIs in detail, with relevant code examples used throughout. The original German book on which this title is based was well received. The NetBeans Platform Community has put together this English translation, which author Heiko Bock updated to cover the latest NetBeans Platform 6.5 APIs. With an introduction by known NetBeans Platform experts Jaroslav Tulach, Tim Boudreau, and Geertjan Wielenga, this is the most up-to-date book on this topic at the moment. Al
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