Data integration in microbial genomics ... - Jacobs University

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100 8. Conclusion and outlook plinary approach allows ecosystems modelling in great detail and on a global scale. The microbial component in the Earth’s biosphere is profoundly understood. Sequencing of environmental data will happen in a high frequency and high throughput manner and realtime monitoring becomes possible. The sequence data is contextualized with high resolution, environmental measurements in realtime, so that the impact of human alterations can be monitored. Global changes can be predicted and steered. The outbreak of epidemics and pandemics can be predicted and prevented. Identifying and locating microorganisms that perform thermodynamically interesting metabolic processes is easy. Studies of microbial genomes will be complemented with knowledge, derived from environmental metagenomic studies. The study of these processes leads to many useful industrial applications that help to solve agricultural and medical problems. New ways to recycle waste and to produce energy will be discovered. Ultimately, breakthroughs in life science help mankind to return to a balanced way of using planet Earth’s resources.
Bibliography [Ackoff, 1989] Ackoff, R. (1989). From data to wisdom. Journal of Applied Systems Analysis, 16:3–9. [Altschul et al., 1990] Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990). Basic local alignment search tool. J Mol Biol, 215(3):403–410. [Amann, 2000] Amann, R. (2000). Who is out there? microbial aspects of biodiversity. Syst Appl Microbiol, 23(1):1–8. [Amann et al., 1995] Amann, R. I., Ludwig, W., and Schleifer, K. H. (1995). Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev, 59(1):143–169. [Anonymous, 2009] Anonymous (2009). Metagenomics versus moore’s law. Nature Methods, 6(9):623–623. [Arrigo, 2005] Arrigo, K. R. (2005). Marine microorganisms and global nutrient cycles. Nature, 437(7057):349–355. [Bateman et al., 2010] Bateman, A., Coggill, P., and Finn, R. D. (2010). Dufs: families in search of function. Acta Crystallogr Sect F Struct Biol Cryst Commun, 66(Pt 10):1148–1152. [Benson et al., 2008] Benson, D. A., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., and Wheeler, D. L. (2008). Genbank. Nucleic Acids Res, 36(Database issue):D25–D30. [Berthel, 1975] Berthel, J. (1975). Information, in: Handwörterbuch der Betriebswirtschaftslehre, volume Bd. 2, 4. Auflage. E. Grochla und W. Wittmann.
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Max Planck Institute for Marine Mic
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List of abbreviations BLAST Basic L
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Thesis abstract Deoxyribonucleic ac
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4.2 Introduction . . . . . . . . .
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2 1. Introduction syntax: data leve
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4 1. Introduction used to derive ne
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18 1. Introduction Doug Wendel, Owe
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CHAPTER 2 METABAR A tool for consis
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2.2. Background 23 molecular sequen
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2.2. Background 25 printing of data
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2.4. Results 27 KML export function
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2.4. Results 29 Figure 2.3: Screens
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2.5. Discussion 31 taking samples i
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2.5. Discussion 33 Handlebar MetaBa
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2.6. Conclusion 35 rine Microbiolog
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2.6. Conclusion 37 RK advised progr
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44 3. CDinFusion tiFASTA file with
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