76,260 research outputs found
A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study
No full textAlbaum S, Hahne H, Otto A, et al. A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study. Proteome Science. 2011;9(1): 30.Background:
Mass spectrometry-based proteomics has reached a stage where it is possible to comprehensively analyze the whole proteome of a cell in one experiment. Here, the employment of stable isotopes has become a standard technique to yield relative abundance values of proteins. In recent times, more and more experiments are conducted that depict not only a static image of the up- or down-regulated proteins at a distinct time point but instead compare developmental stages of an organism or varying experimental conditions.
Results:
Although the scientific questions behind these experiments are of course manifold, there are, nevertheless, two questions that commonly arise: 1) which proteins are differentially regulated regarding the selected experimental conditions, and 2) are there groups of proteins that show similar abundance ratios, indicating that they have a similar turnover? We give advice on how these two questions can be answered and comprehensively compare a variety of commonly applied computational methods and their outcomes.
Conclusions:
This work provides guidance through the jungle of computational methods to analyze mass spectrometry-based isotope-labeled datasets and recommends an effective and easy-to-use evaluation strategy. We demonstrate our approach with three recently published datasets on Bacillus subtilis [1,2] and Corynebacterium glutamicum [3]. Special focus is placed on the application and validation of cluster analysis methods. All applied methods were implemented within the rich internet application QuPE [4]. Results can be found at http://qupe.cebitec.uni-bielefeld.de webcite
Flexible metagenome analysis using the MGX framework
No full textJaenicke S, Albaum S, Blumenkamp P, Linke B, Stoye J, Goesmann A. Flexible metagenome analysis using the MGX framework. Microbiome. 2018;6(1): 76
International marketing and export management / Gerald Albaum, Edwin Duerr.
No full textIncludes bibliographical references and index.xxxi, 990 p. :International Marketing and Export Management 7th edition offers an accessible and authoritative perspective on international marketing with a strong export management orientation, comprehensively describing the evolving competitive landscape as created by technological advances and international trade patterns. The seventh edition retains its clear and informed coverage of the opportunities for companies of all sizes and in all industries in the export of goods, services, intellectual property and business models
Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii
No full textToepel J, Albaum S, Arvidsson S, et al. Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii. BMC Genomics. 2011;12(1): 579.ABSTRACT: BACKGROUND: Chlamydomonas reinhardtii is widely accepted as a model organism regarding photosynthesis, circadian rhythm, cell mobility, phototaxis, and biotechnology. The complete annotation of the genome allows transcriptomic studies, however a new microarray platform was needed. Based on the completed annotation of Chlamydomonas reinhardtii a new microarray on an Agilent platform was designed using an extended JGI 3.1 genome data set which included 15000 transcript models. RESULTS: In total 44000 probes were determined (3 independent probes per transcript model) covering 93% of the transcriptome. Alignment studies with the recently published AUGUSTUS 10.2 annotation confirmed 11000 transcript models resulting in a very good coverage of 70% of the transcriptome (17000). Following the estimation of 10000 predicted genes in Chlamydomonas reinhardtii our new microarray, nevertheless, covers the expected genome by 90-95%. CONCLUSIONS: To demonstrate the capabilities of the new microarray, we analyzed transcript levels for cultures grown under nitrogen as well as sulfate limitation, and compared the results with recently published microarray and RNA-seq data. We could thereby confirm previous results derived from data on nutrient-starvation induced gene expression of a group of genes related to protein transport and adaptation of the metabolism as well as genes related to efficient light harvesting, light energy distribution and photosynthetic electron transport
Portrait of Amy Mack (Mrs Lancelot Harrison) [picture] /
No full textTitle from inscription on reverse.; Condition: Fair, glued to card.; Inscriptions: "Amy Mack (Mrs. Lancelot Harrison) author of 'A bush calendar', 'Bush days', etc. photo. J. S. P. Ramsay" --In ink on reverse
Profiling of Soluble Neutral Oligosaccharides from Treated Biomass using Solid Phase Extraction and Liquid Chromatography-Multiplexed Collision Induced Dissociation-Mass Spectrometry
No full textThermochemical pretreatment of cellulosic biomass improves cell wall enzymatic digestibility, while simultaneously releasing substantial amounts of soluble oligosaccharides. Profiling of oligosaccharides released during pretreatment yield information essential for choosing glycosyl hydrolases necessary for cost-effective conversion of cellulosic biomass to desired biofuel/biochemical end-products. In this report we present a methodology for profiling of soluble neutral oligosaccharides released from ammonia fiber expansion (AFEXTM)-pretreated corn stover. Our methodology employs solid phase extraction (SPE) enrichment of oligosaccharides based on porous graphitized carbon (PGC), followed by high performance liquid chromatography (HPLC) separation using a polymeric amine based column (Prevail Carbohydrate ES) and electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) in both positive and negative modes. For structural elucidation on the chromatographic time scale, nonselective multiplexed collision-induced dissociation was performed for quasi-simultaneous acquisition of accurate molecular and fragment masses of neutral oligosaccharids in a single analysis. These analyses directly revealed presence of glucans up to degree of polymerization (DP) 22 without side-chain modifications. Additionally, arabinoxylans with DP up to 6 were detected in the pretreated biomass samples (post-enzymatic digestion). All linkages between sugar units in glucans and arabinoxylans were identified to be p-1-4 linkages based on cross-ring fragment masses. Comprehensive profiling of soluble oligosaccharides also demonstrated that arabinoxylan acetylation was reduced by greater than 85% post-AFEXTM treatment.Published version: Vismeh, Ramin, Humpula, James F., Chundawat, Shishir P. S., Balan, Venkatesh, Dale, Bruce E. & Jones, A. Daniel. (2013). Profiling of Soluble Neutral Oligosaccharides from Treated Biomass using Solid Phase Extraction and LC-TOF MS. Carbohydrate Polymers 94(2), 791-799. http://dx.doi.org/10.1016/j.carbpol.2013.02.00
EMMA 2-A MAGE-compliant system for the collaborative analysis and integration of microarray data
No full textDondrup M, Albaum S, Griebel T, et al. EMMA 2-A MAGE-compliant system for the collaborative analysis and integration of microarray data. BMC Bioinformatics. 2009;10(1): 50.Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Experimental study of thin film sensor networks for wind turbine blade damage detection
No full textDamage detection of wind turbine blades is difficult due to their complex geometry and large size, for which large deployment of sensing systems is typically not economical. A solution is to develop and deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel skin-type strain gauge for measuring strain over very large surfaces. The skin, a type of large-area electronics, is constituted from a network of soft elastomeric capacitors. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a dense network of soft elastomeric capacitors to detect, localize, and quantify damage on wind turbine blades. We also leverage mature off the shelf technologies, in particular resistive strain gauges, to augment such dense sensor network with high accuracy data at key locations, therefore constituting a hybrid dense sensor network. The proposed hybrid dense sensor network is installed inside a wind turbine blade 1:25 scale model, and tested in a wind tunnel to simulate an operational environment. Results demonstrate the ability of the hybrid dense sensor network to detect, localize, and quantify damage.</p
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