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217 Operands also include named sets, which can either be databank names (all entries from the databank of the given name) or results of previously evaluated queries. For instance the query: (temp=[embl-org:human])>SWISSPROT | temp > SWISSNEW defines a temporary set named “temp” and links it to two databanks named SWISSPROT [7] and SWISSNEW. If A and B are sets of entries of two linked databanks, the query “A>B” will return all the entries in the set B, which are linked to one or more entries in A. The link operation is antisymmetric, i.e. “A>B” is equivalent to “Bparent” will return all databank entries containing the subentries in S. Note that each different databank contains usually different types of data. In a certain way each databank behaves as an extent of a class in an object oriented databases. The link between two databanks has a different meaning depending on the databanks involved. For example, the query “SWISSPROT
218 database management systems. The join operator is used to logically combine tuples from two relations into single tuples, however the link operators select entries from one databank that are linked to entries of another databank. Link operations are much less CPU-intensive than joins especially if one of the two linked databanks is very large. SRS Interfaces Several different interfaces to SRS are available. The C-API facilitates the full use of SRS’s capabilities to those interested in accessing function libraries for programming purposes. The second interface is a UNIX based command-line interface named ‘getz’. Getz provides a more direct querying mechanism, and also implicitly allows its combination with other computer applications and UNIX commands. This allows powerful retrieval on a larger scale via automation as well as interfacing with other bioinformatics programs. The SRS Web interface is, however, by far the most popular interface in use. Although less powerful, it’s user-friendly design has made SRS accessible to a much wider section of the scientific community. SRSWWW – The Web Interface to SRS A major difference between SRSWWW [9] and most Web services is that it maintains state [10]. In effect, users start a session within SRSWWW, at which point they are designated a unique identifier by the SRS server. After the session is completed, it may be ‘bookmarked’ within the Web browser. This allows the return of the user at a later time to the same point in the previous session. At present, the session is removed from the system after two days if it is not accessed again. This will be extended to an unlimited time period in the next SRS release due to increasing request for truly permanent sessions. This will also allow sessions to be downloaded and moved between different sites. After entering a new SRS session the user enters the ‘Top Page’ (see figure 1). Initially, the user is requested to select at least one of the databanks offered which are grouped into categories. In addition to the inclusion of biological databases such as genome, mapping and transcription factor databases, more diverse areas such as mutation databanks are now accessible through SRS.
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BIOINFORMATICS: Databases and Syste
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BIOINFORMATICS: Databases and Syste
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To Tish, Emily, Miles and Josephine
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TABLE OF CONTENTS INTRODUCTION ....
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INTRODUCTION Stanley Letovsky Bioin
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for wisdom. Where algorithms tend t
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gain performance by distributing qu
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systems described (OPM, BioKleisli,
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DATABASES
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1 NCBI: INTEGRATED DATA FOR MOLECUL
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figure 1, and all flows into the ID
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There are other sets of data that c
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2. Explicit declaration by the hist
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2. W. J. Wilbur, A retrieval system
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2 HOVERGEN: COMPARATIVE ANALYSIS OF
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Figure 1: Phylogenetic tree of the
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fragment. In some cases, a same gen
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Figure 2: Distribution of families
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the user can visualize all the anno
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Selecting orthologous genes with HO
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Thus, HOVERGEN allows one to do exh
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21. Saitou, N. Nei, M. The neighbor
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3 WIT/WIT2: METABOLIC RECONSTRUCTIO
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protein sequence are used (e.g., OR
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After we have accumulated an initia
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Coordinating the Development of Met
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Availability of the Pathways, Softw
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4 ECOCYC: THE RESOURCE AND THE LESS
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epresented as an instance of the cl
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The Gene--Reaction Schematic The ma
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EcoCyc contains extensive informati
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within compound windows uses a conc
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Figure 4: The EcoCyc linear map bro
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Figure 5: The software architecture
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6. Karp. Frame representation and r
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Introduction 5 KEGG: FROM GENES TO
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Binary relations Figure 1 : Level o
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hierarchical text. The genome map i
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(2) Java applets to search, compare
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can be used for gene function assig
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influenzae lacks the upper portion
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Future Directions Figure 4. KEGG as
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Introduction 6 OMIM: ONLINE MENDELI
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The Entry Each OMIM entry is assign
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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
Page 176 and 177: Figure 2 : Main AGIS Menu 167
Page 178 and 179: Figure 4 : Available Classes and Su
Page 180 and 181: Figure 6 : Query by Example and Que
Page 182 and 183: Figure 8 : Hypertext ACEDB Object a
Page 184 and 185: 15 CGSC: THE E.COLI GENETIC STOCK C
Page 186 and 187: 177 described once for that gene an
Page 188 and 189: FIGURE 1. A Query for an hsdR- recA
Page 190 and 191: FIGURE 2. A Query for a lacZ-(amber
Page 192 and 193: 183 These are suggestions that dese
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Page 196 and 197: Introduction 16 OPM: OBJECT-PROTOCO
Page 198 and 199: 189 OPM is a data model whose objec
Page 200 and 201: The OPM Database Development Tools
Page 202 and 203: ased on this query tree. Further qu
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Page 206 and 207: 197 Our strategy of providing suppo
Page 208 and 209: Acknowledgments 199 Between 1992 an
Page 210 and 211: Introduction 17 BIOKLEISLI:INTEGRAT
Page 212 and 213: 203 In the remainder of this chapte
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Page 216 and 217: BioKleisli in Action: Querying Biom
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Page 220 and 221: References 211 13. NCBI ASN. 1 Spec
Page 222 and 223: Introduction 18 SRS: ANALYZING AND
Page 224 and 225: 215 In SRS, databank structures are
Page 228 and 229: Figure 1. The SRS Top Page. Figure
Page 230 and 231: Analyzing Data in SRS with Applicat
Page 232 and 233: 223 other databanks, and define spe
Page 234 and 235: Figure 7. A SWISS-PROT entry with i
Page 236 and 237: Figure 8. The results of a query fo
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Page 240 and 241: 23 1 12. Altschul, S.F., Gish, W.,
Page 242 and 243: Introduction 19 BIOLOGY WORKBENCH:
Page 244 and 245: Figure 1. Organization and Flow of
Page 246 and 247: 237 In order to make wrapper develo
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Page 252 and 253: PROFILESCAN Comparison of protein o
Page 254 and 255: 20 EBI: CORBA AND THE EBI DATABASES
Page 256 and 257: 247 the Object Request Broker (ORB)
Page 258 and 259: 249 Every database entry is represe
Page 260 and 261: 251 Wrappers with and without State
Page 262 and 263: Discussion 25 3 CORBA and IDL minim
Page 264 and 265: Introduction 21 BIOWIDGETS:REUSABLE
Page 266 and 267: Visualization Solutions 257 Turnkey
Page 268 and 269: 259 The architecture also exploits
Page 270 and 271: possible because the bioWidget arch
Page 272 and 273: 263 4. Gish, Warren (1994-1997). un
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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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