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Figure 4 : Available Classes and Sublist Selection Pages for RiceGenes Query Mode 169 Selecting query mode brings the user to a form allowing the databases to be searched/queried by six different methods, including fuzzy search, WAIS, Query by Example, Query Builder, Table-maker, and ACEDB Query Language in which an ACEDB query can be input directly. ACEDB query. This mode is extremely fast and efficient for data retrieval, but it does require the user to be familiar with the ACEDB query language as well as the data structure of the particular database. While these two topics are outside the scope of the current paper, the reader is referred to several excellent treatises on the ACEDB query language [7,8], available at the AGIS site.
170 Figure 5 : ACEDB Query Interface Figure 5 shows the basic ACEDB query interface. The query is typed into the form and submitted, and a hypertext ACEDB object is returned. Fuzzy (AGREP) and WAIS query. The fuzzy and WAIS modes present the simplest query interface. One or more words can be entered as the search string, and wildcards are accepted. A search returns a hypertext list of database objects. Query by Example. This mode allows the user to query one class of a database by typing search strings into one or more field categories on a form. The query brings back a list of matching objects. Figure 6 shows the Query by Example interface to the GeneFamily class of the Mendel database.
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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
Page 128 and 129: 10 THE MOUSE GENOME DATABASE AND TH
Page 130 and 131: genetics community fostered the ear
Page 132 and 133: 123 Data acquisition for MGD includ
Page 134 and 135: 125 In February 1998, a ‘cDNA and
Page 136 and 137: Acknowledgments 127 MGD is funded b
Page 138 and 139: 11 THE EDINBURGH MOUSE ATLAS: BASIC
Page 140 and 141: expression database under developme
Page 142 and 143: 133 For blastocysts the shape of th
Page 144 and 145: 135 which is a cut at an arbitrary
Page 146 and 147: 137 This defines a viewing directio
Page 148 and 149: 139 plate spline [19] or polynomial
Page 150 and 151: 12 FLYBASE: GENOMIC AND POST- GENOM
Page 152 and 153: 143 Genes, including links via publ
Page 154 and 155: Public Access to FlyBase Data The c
Page 156 and 157: 147 There are two classes of annota
Page 158 and 159: 149 screens to identify direct or i
Page 160 and 161: 13 MAIZEDB: THE MAIZE GENOME DATABA
Page 162 and 163: The bins map strategy has been empl
Page 164 and 165: Clicking on one of the orthologous
Page 166 and 167: * hyper-text linked to MaizeDB enti
Page 168 and 169: DISSEMINATION TO EXTERNAL DATABASES
Page 170 and 171: Appendix 2: part of the Query Form
Page 172 and 173: Introduction 14 AGIS: USING THE AGR
Page 174 and 175: Horn Fly--Haematobia Screwworm--Coc
Page 176 and 177: Figure 2 : Main AGIS Menu 167
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
Page 194 and 195: SYSTEMS
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
Page 204 and 205: 195 Interface, except that one can
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
Page 214 and 215: pages : “4267-4274", abstract:
Page 216 and 217: BioKleisli in Action: Querying Biom
Page 218 and 219: 209 savings in execution time is si
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 226 and 227: 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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