Computational tools and Interoperability in Comparative ... - CBS

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Chapter 4 Web Services and Interoperability in Genomics Web Services and Interoperability in Genomics This chapter describes work done connection with the EU project EMBRACE. The deliverables defined for CBS have had both outreach obligations as well as implementation tasks of providing tools and databases through Web Services. This author’s contributions reflect this duality; there was a responsibility for developing the server infrastructure for hosting Web Services while also teaching about using and design concepts on several occasions (see appendix A.1). CBS is now using this work to integrate all major prediction servers under the same Web Services umbrella. There are currently 17 services offered using this technology 1 . The work on Web Services has made the foundation for creating an online resource like BLASTatlas (paper I). Further, the RNAmmer tool (VI) is offered both as a traditional web interface and through Web Services and these implementations demonstrate the usefullness of programmtic access to tools. 4.1 Introduction Over the past decade, the internet has undoubtedly revolutionized the way information is exchanged in the modern society. From bank transactions, digital road maps and satellite images, emailing, news articles, and social networks, these services are now hard to imagine, without a digitally connected world. Biological and bioinformatic information is no exception as it relies on the internet to provide the transport of sequence data, experimental results, scientific articles etc. Both the number and complexity of biological information increases day by day. As new experimental techniques become available, new types of data as well as new ways of combining them, are introduced. For decades, the exchange of biological information over the internet has been in the form of human readable HTML documents (HyperText Markup Language) - or flat files residing on FTP servers (File Transfer Protocol). When designed, HTML was intended to host static information presented by a server to a human being using a browser. Today, computers are required to digest the huge amounts of information with less involvement of humans, and more advanced technologies are now required. To successfully integrate the vast amounts of data provided by the life science community, interoperability remains a key issue. It may seem unrealistic to reach a point where every biologist and bioinformatician has the world’s biological databases and tools accessible through programmatic access, from their favorite programming language. However, with the current technologies in Web 1 BLASTatlas, EasyGene, EPipe, GeneWiz, GenomeAtlas, hERG, MaxAlign, NetChop, NetCTL, Net- Glycate, NetNGlyc, NetOGlyc, NetPhos, RNAmmer, SIDDbase, SignalP, and TMHMM 145
Interoperability Figure 4.1: Screen shot of NCBI Entrez Genome projects web page Services, an interoperble life science community may not be far away. When connected, the communities will be able to exchange not only data but many services such as tools for predicting protein function, performing sequence alignments, or gene finding. 4.2 Interoperability ”The term ’interoperability’ is defined as the ability ... information, by IEEE (http...)”. The term ’interoperability’ is defined as the ability of two or more systems to exchange and make use of information (IEEE, http://www.ieee.org). Whether systems can be said to be ’interoperable’ depends on how one interprets ’make use of’. Consider the list of full prokaryotic genome sequences, maintained by NCBI at http://www.ncbi.nlm.nih. gov/genomes/lproks.cgi, as shown in figure figure 4.1. To automatically retrieve this list, one may write a parser to transform the HTML into a computer-readable text. Apart from being overly sensitive to changes in the HTML document, such a parser will lack the knowledge behind the data since the format is not typed nor structured. It is only when interpreted by an internet browser and presented graphically to a human, that this information makes any sense. Both recipient and receiver must in other words have knowledge about the information that is exchanged, before these can be said to be interoperable. The are two aspects of interoperability: First, there must exist agreement on the format by which data is exchanged. Whether this is structured XML or any arbitrary format, the server must return the format expected by the client upon a request. Second, the description and understanding of the content of the data being exchanged is a requirement when building client-side code and objects in Web Services. Without the knowledge of exact data types, the programming environment (e.g. C, Java, Perl) fails to declare the objects with proper variable types. 146
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Peter Fischer Hallin | 2009 Peter F
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Preface This Ph.D. thesis is writte
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thesis, the work is just being publ
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ved at blive publiceret i Standards
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viii
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Paper VI [Lagesen K, Hallin P] 1 ,
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3.3.3 Refining E. coli and Shigella
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xviii 2.17 Pan- and core-genome plo
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Chapter 1 Introduction Introduction
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Chapter 2 Comparative Genomics 2.1
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Comparative Genomics the publicly a
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Comparative Genomics source CDS tot
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Comparative Genomics 1 mysql -N -B
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Listing 2.8: R code to generate a 2
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1st U C A G U 2nd position C A G 3r
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1st U C A G U 2nd position C A G 3r
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Escherichia coli strain K-12, subst
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Comparative Genomics
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3M 2.5M 3.5M 2.5M 2M 0M 2M 0.5M B.
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Streptococcus Escherichia Bacillus
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2.4 Summary Comparative Genomics Th
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Comparative Genomics 2.5 Instant in
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‘ReSourCe is he best online submi
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up to a total of 41 different E. co
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Fig. 2 Genes (or segments) from eac
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Fig. 5 BLASTatlas of Clostridium bo
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different applications, such as ide
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1 Comparative Genomics 2.7 Paper II
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166 literally millions of bacterial
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168
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170 resistance genes on mobile gene
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172 involved in generating diversit
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174 recipient DNA. A feature observ
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176 Fig. 5 Genome length distributi
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178
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180 reasons why organisms remain un
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182 A final problem has to do with
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184 Middendorf B, Hochhut B, Leipol
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1 Comparative Genomics 2.8 Paper II
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2 O. N. Reva et al. Fig. 1. Genome
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4 O. N. Reva et al. decrease of the
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6 O. N. Reva et al. of which are kn
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8 O. N. Reva et al. compiled into a
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10 O. N. Reva et al. encoded by a c
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12 O. N. Reva et al. systems and ef
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1 2.9 Paper IV: The origins of Vibr
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phylogenies based on alternative ho
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Figure 1 Phylogenetic tree of the 1
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25000 20000 15000 10000 5000 0 Pan
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Gap F 2M 2.5M Gap E 875k 750k 625k
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Table 2 A selection of genes locate
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Open Access This article is distrib
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1 Comparative Genomics 2.10 Paper V
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4314 74 Tools Abstract: Of the plet
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4316 74 Tools Size distribution of
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Page 164 and 165: ing platform-‐independent Java
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Page 180 and 181: Appendix A Appendix: Workshops, tea
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Page 196 and 197: Appendix: Software 25 [ ] A l t e r
Page 198 and 199: BIBLIOGRAPHY J. Rogers, P. F. Stadl
Page 200 and 201: BIBLIOGRAPHY Q. Jin, Z. Yuan, J. Xu
Page 202 and 203: BIBLIOGRAPHY Velicer, F.-J. Vorholt
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