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249 Every database entry is represented by a “struct”. In contrast to CORBA objects, structs are passed by value. Access to the individual fields is therefore local and very fast. On the other hand the application has to get the whole struct even if it is only interested in the sequence field. Structs are nearly as convenient to use as CORBA objects with one subtle difference. Structs can’t be referenced physically. In this example the SwissProt entry contains the accession number of an EMBL entry. The client has to know itself how to get the EMBL sequence given the accession number. The upcoming CORBA 3.0 specification will address the pass-by-value issue and make the definition of structs unnecessary in some cases. Generic In this approach the data model is not represented in IDL. The objects are instead encoded in generic types like strings. The main advantage of this approach is ease of maintenance. Using IDL, clients and servers have to be compiled together with the classes, which are generated from the IDL definition. This can become a burden if the data model is large or changes frequently. Generic representations are well suited for generic applications, which are not interested in the semantics of the data. For end-user applications (e.g. an alignment program) generic representations are very cumbersome to use. An example of a syntax of this sort is the object interchange format OIF, defined in the ODMG 2.0 standard [4]. Queries The ability to express queries is important for all databases. This aspect is standardized in CORBA through the query service specification [10]. The central element is a CORBA object of the type query evaluator. A query evaluator takes a query string as input and returns a reference to a result collection. This collection is another CORBA object, which can itself implement the query evaluator interface. Because the query service does not specify the elements of the result collection, it can be combined with any of the above listed representations. Furthermore the query service can be used with every possible query language depending on the underlying database management system. Conceptual Data Model Even though Interface-Based and Struct-Based representations can have a very strong similarity to the conceptual data model, it is important not to confuse them. The purpose of the conceptual model is to model the data as they really are, using concepts close to humans. Neither the database schema nor the IDL can replace such a high level model. The database schema is specific to the used DBMS and may contain optimizations. The IDL is independent from implementation details but it represents merely an application specific view.
250 CORBA Wrappers Figure 2: Relationship of Conceptual Model, DB Schema and IDL Generally, today’s databases do not provide CORBA interfaces to their data. It is therefore necessary to build a so-called wrapper – a program which implements IDL interfaces for already existing “legacy systems”. This section will discuss some of the technical issues involved for a fine-grained CORBA interface. Figure 3: CORBA wrappers make existing DBs available through the ORB Registering Large Numbers of Objects Databases can contain millions of entries. The ORB has to be able to keep track of the connection between these database entries and the corresponding CORBA object references. The general idea is to encode a unique identifier of the database entry in the object reference. It is therefore essential that such an object identifier or key attribute exists in the database. Most ORBs have their own proprietary way of implicitly registering large numbers of objects. The recently adopted Portable Object Adapter (POA) standardizes this possibility.
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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
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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
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 226 and 227: 217 Operands also include named set
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 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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Page 276 and 277: 267 On the other hand, most users c
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Page 282 and 283: 273 database the class Map refers t
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Page 288 and 289: Introduction 23 LABBASE: DATA AND W
Page 290 and 291: 28 1 We will use as a running examp
Page 292 and 293: LabBase Details 283 A LabBase objec
Page 294 and 295: When the procedure completes, LabFl
Page 296 and 297: 287 sequence-assembly Worker in our
Page 298 and 299: 289 The Worker converts the object
Page 300 and 301: 291 Genome Research and are beginni
Page 302 and 303: INDEX
Page 304 and 305: INDEX A of Agricultural Genome Info
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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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