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Thus, HOVERGEN allows one to do exhaustive searches of orthologous genes, but not of paralogous genes. It should be noted that alignments provided by HOVERGEN are crude results from CLUSTALV, without any manual correction. Moreover, when calculating phylogenetic trees, one should exclude ambiguous parts of the alignment, which cannot be done in our automatic procedure. We also have noted some problems in phylogenetic trees (such as negative branches) that are due to the fact that we include partial sequences in our classification. Thus, although trees provided by HOVERGEN are very useful for analyzing evolutionary relationships, one should not take them as exact phylogenetic trees. Perspectives Up to now, HOVERGEN was limited to vertebrates, but we plan to extend this database to all organisms. The classification will be exhaustive, so that it will be possible to systematically analyze not only orthologues but also paralogues. This new database will be based both on GenBank/EMBL (for DNA sequences), and on SWISSPROT-TREMBL [37] to have access to high quality annotations for protein sequences. The graphical interface of this system is being written in Java, so that it will be possible to use it from any computer system for which the Java Virtual Machine is available. Also, as the Java libraries include tools allowing simple INTERNET connections and client/server interactions, it will be possible to query this database either locally or remotely. Availability HOVERGEN is available by anonymous FTP from our server (ftp://biom3.univ- lyon1.fr/pub/hovergen/) or from the NCBI (ftp://ncbi.nlm.nih.gov/repository/hovergen/). The QUERY_WIN program and HOVERGEN graphical interface are available for UNIX platforms (Sun, SGI, DEC- Alpha, IBM-RS/6000). HOVERGEN can be used through the Web at: http://acnuc.univ-lyonl.fr/start.html/. It is also possible to ask for an account at the UK MRC HGMP Resource Centre (http://www.hgmp.mrc.ac.uk/) or at the French INFOBIOGEN server (http://www.infobiogen.fr/) to use HOVERGEN remotely with a X-window emulating software. Acknowledgments This work is supported by the French Centre National de la Recherche Scientifique (CNRS). 33
34 References 1. Hood, L., Koop, B., Goverman, J. Hunkapiller, T. Model genomes: the benefits of analysing homologous human and mouse sequences, Trends Biotechnol., 1992, 10, pp.19-22. 2. Brenner, S., Elgar, G., Sandford, R., MacRae, A., Venkatesh, B. Aparicio, S. Characterization of the pufferfish (Fugu) genome as a vertebrate genome, Nature, 1993, 366, pp.265-268. compact model 3. Makalowski, W., Zhang, J.H. Boguski, M.S. Comparative analysis of 1196 orthologous mouse and human fill-length mrna and protein sequences, Genome Res., 1996, 6, pp.846-857. 4. Benson, D.A., Boguski, M.S., Lipman, D.J. Ostell, J. GenBank, Nucleic Acids Res., 1997, 25, pp.1-6. 5. Stoesser, G., Sterk, P., Tuli, M.A., Stoehr, P.J. Cameron, G.N. The EMBL Nucleotide Sequence Database, Nucleic Acids Res., 1997, 25, pp.7-13. 6. Duret, L., Mouchiroud, D. Gouy, M. HOVERGEN: a database of homologous vertebrate genes, Nucleic Acids Res., 1994, 22, pp.2360-2365. 7. Fitch, W.M. Distinguishing homologous from analogous proteins, Syst. Zool., 1970, 19, pp.99-113. 8. Doolittle, R.F. Convergent evolution: the need to be explicit, Trends Biochem. Sci., 1994, 19, pp.15-18. 9. Wootton, J.C. Federhen, S. Statistics of local complexity in amino acid sequences and sequence databases, Computers Chem., 1993, 17, pp. 149-163. 10. Doolittle, R.F. Searching through sequence databases, Methods Enzymol., 1990, 183, pp.99-110. 11. Patthy, L. Modular exchange principles in proteins, Curr. Opin. Struct. Biol., 1991,1, pp.351-361. 12. Patthy, L. Introns and exons, Curr. Opin. Struct. Biol., 1994, 4, pp.383-392. 13. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. Lipman, D.J. Basic local alignment search tool, J. Mol. Biol., 1990, 215, pp.403-410. 14. Pearson, W.R. Lipman, D.J. Improved tools for biological sequence comparison, Proc. Natl. Acad. Sci. USA, 1988, 85, pp.2444-2448. 15. Li, W.H. Sadler, A. Low nucleotide diversity in man, Genetics, 1991, 129, pp.513-523. 16. Krawetz, S.A. Sequence errors in GenBank: a means to determine the accuracy of DNA sequence interpretation, Nucleic Acids Res., 1989, 17, pp.3951-3957. 17. Kristensen, T., Lopez, R. Prydz, H. An estimate of the sequencing error frequency in the DNA sequence databases, DNA Seq., 1992, 2, pp.343-346. 18. Lamperti, E.D., Kittelberger, J.M., Smith, T.F. Villa-Komaroff, L. Corruption of genomic databases with anomalous sequence, Nucleic Acids Res., 1992, 20, pp.2741-2747. 19. Sokal, R.R. Michener, C.D. A statistical method for evaluating systematic relationships, Univ. Kansas Sci. Bull., 1958, 28, pp.1409-1438. 20. Higgins, D.G., Bleasby, A.J. Fuchs, R. CLUSTAL V: imp roved software for multiple sequence alignment, Comp. Appl. Biosci., 1992, 8, pp.189-191.
Page 2 and 3: BIOINFORMATICS: Databases and Syste
Page 4 and 5: BIOINFORMATICS: Databases and Syste
Page 6 and 7: To Tish, Emily, Miles and Josephine
Page 8 and 9: TABLE OF CONTENTS INTRODUCTION ....
Page 10 and 11: INTRODUCTION Stanley Letovsky Bioin
Page 12 and 13: for wisdom. Where algorithms tend t
Page 14 and 15: gain performance by distributing qu
Page 16 and 17: systems described (OPM, BioKleisli,
Page 18 and 19: DATABASES
Page 20 and 21: 1 NCBI: INTEGRATED DATA FOR MOLECUL
Page 22 and 23: figure 1, and all flows into the ID
Page 24 and 25: There are other sets of data that c
Page 26 and 27: 2. Explicit declaration by the hist
Page 28 and 29: 2. W. J. Wilbur, A retrieval system
Page 30 and 31: 2 HOVERGEN: COMPARATIVE ANALYSIS OF
Page 32 and 33: Figure 1: Phylogenetic tree of the
Page 34 and 35: fragment. In some cases, a same gen
Page 36 and 37: Figure 2: Distribution of families
Page 38 and 39: the user can visualize all the anno
Page 40 and 41: Selecting orthologous genes with HO
Page 44 and 45: 21. Saitou, N. Nei, M. The neighbor
Page 46 and 47: 3 WIT/WIT2: METABOLIC RECONSTRUCTIO
Page 48 and 49: protein sequence are used (e.g., OR
Page 50 and 51: After we have accumulated an initia
Page 52 and 53: Coordinating the Development of Met
Page 54 and 55: Availability of the Pathways, Softw
Page 56 and 57: 4 ECOCYC: THE RESOURCE AND THE LESS
Page 58 and 59: epresented as an instance of the cl
Page 60 and 61: The Gene--Reaction Schematic The ma
Page 62 and 63: EcoCyc contains extensive informati
Page 64 and 65: within compound windows uses a conc
Page 66 and 67: Figure 4: The EcoCyc linear map bro
Page 68 and 69: Figure 5: The software architecture
Page 70 and 71: 6. Karp. Frame representation and r
Page 72 and 73: Introduction 5 KEGG: FROM GENES TO
Page 74 and 75: Binary relations Figure 1 : Level o
Page 76 and 77: hierarchical text. The genome map i
Page 78 and 79: (2) Java applets to search, compare
Page 80 and 81: can be used for gene function assig
Page 82 and 83: influenzae lacks the upper portion
Page 84 and 85: Future Directions Figure 4. KEGG as
Page 86 and 87: Introduction 6 OMIM: ONLINE MENDELI
Page 88 and 89: The Entry Each OMIM entry is assign
Page 90 and 91: Searching OMIM is as simple as typi
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How OMIM is Curated OMIM is maintai
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7 GDB: INTEGRATING GENOMIC MAPS Int
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in one of two ways: by being wholly
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Figure 3: Universal Coordinate Disp
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Figure 5: Dispersion of linear (lef
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which minimizes dispersion. The opt
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Figure 10: A piece of an "comprehen
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alignments are better for the speci
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Summary 8 HGMD: THE HUMAN GENE MUTA
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Data coverage and structure 101 By
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Conclusions and Outlook 103 Being b
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Introduction 9 SENSELAB: MODELING H
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107 For the purposes of the rest of
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109 users might advocate creating a
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111 The Associations table describe
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Managing the Object Class Hierarchy
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115 In fig. 2, the Objects and Clas
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117 7. Mirsky JS, Nadkarni PM, Hine
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10 THE MOUSE GENOME DATABASE AND TH
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genetics community fostered the ear
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123 Data acquisition for MGD includ
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125 In February 1998, a ‘cDNA and
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Acknowledgments 127 MGD is funded b
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11 THE EDINBURGH MOUSE ATLAS: BASIC
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expression database under developme
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133 For blastocysts the shape of th
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135 which is a cut at an arbitrary
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137 This defines a viewing directio
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139 plate spline [19] or polynomial
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12 FLYBASE: GENOMIC AND POST- GENOM
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143 Genes, including links via publ
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Public Access to FlyBase Data The c
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147 There are two classes of annota
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149 screens to identify direct or i
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13 MAIZEDB: THE MAIZE GENOME DATABA
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The bins map strategy has been empl
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Clicking on one of the orthologous
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* hyper-text linked to MaizeDB enti
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DISSEMINATION TO EXTERNAL DATABASES
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Appendix 2: part of the Query Form
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Introduction 14 AGIS: USING THE AGR
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Horn Fly--Haematobia Screwworm--Coc
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Figure 2 : Main AGIS Menu 167
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Figure 4 : Available Classes and Su
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Figure 6 : Query by Example and Que
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Figure 8 : Hypertext ACEDB Object a
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15 CGSC: THE E.COLI GENETIC STOCK C
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177 described once for that gene an
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FIGURE 1. A Query for an hsdR- recA
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FIGURE 2. A Query for a lacZ-(amber
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183 These are suggestions that dese
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SYSTEMS
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Introduction 16 OPM: OBJECT-PROTOCO
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189 OPM is a data model whose objec
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The OPM Database Development Tools
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ased on this query tree. Further qu
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195 Interface, except that one can
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197 Our strategy of providing suppo
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Acknowledgments 199 Between 1992 an
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Introduction 17 BIOKLEISLI:INTEGRAT
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203 In the remainder of this chapte
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pages : “4267-4274", abstract:
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BioKleisli in Action: Querying Biom
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209 savings in execution time is si
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References 211 13. NCBI ASN. 1 Spec
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Introduction 18 SRS: ANALYZING AND
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215 In SRS, databank structures are
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217 Operands also include named set
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Figure 1. The SRS Top Page. Figure
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Analyzing Data in SRS with Applicat
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223 other databanks, and define spe
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Figure 7. A SWISS-PROT entry with i
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Figure 8. The results of a query fo
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parser and documentation files, and
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23 1 12. Altschul, S.F., Gish, W.,
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Introduction 19 BIOLOGY WORKBENCH:
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Figure 1. Organization and Flow of
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237 In order to make wrapper develo
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the browser window containing a men
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either during the current Workbench
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PROFILESCAN Comparison of protein o
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20 EBI: CORBA AND THE EBI DATABASES
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247 the Object Request Broker (ORB)
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249 Every database entry is represe
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251 Wrappers with and without State
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Discussion 25 3 CORBA and IDL minim
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Introduction 21 BIOWIDGETS:REUSABLE
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Visualization Solutions 257 Turnkey
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259 The architecture also exploits
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possible because the bioWidget arch
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263 4. Gish, Warren (1994-1997). un
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22 ACEDB: THE ACE DATABASE MANAGER
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267 On the other hand, most users c
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269 Street, City and State into "ma
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27 1 to a running database after ed
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273 database the class Map refers t
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275 were waiting for the Biowidget
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277 table of 13 columns and 1 milli
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Introduction 23 LABBASE: DATA AND W
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28 1 We will use as a running examp
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LabBase Details 283 A LabBase objec
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When the procedure completes, LabFl
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287 sequence-assembly Worker in our
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289 The Worker converts the object
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291 Genome Research and are beginni
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INDEX
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INDEX A of Agricultural Genome Info
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of vertebrate genes, 21-33 developm
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GenBank database query software of,
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Metabolic Pathway Database, 38 Meta
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conversion to ‘gi’ identifiers
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