Davidson, S., Overton, C., Tannen, V. & Wong, L. (1997), `BioKleisli: A digital library for biomedical researchers', International Journal of Digital Libraries 1(1), 36--53.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....and maintained in isolation from each other, and thus manifest classical syntactic and semantic heterogeneities. As a result, there has been considerable attention devoted to the development of proposals that ease the task of exploring or accessing heterogeneous bioinformatics resources (e.g. [10, 7, 8]) However, few such proposals have provided truly declarative query interfaces or high levels of transparency. The work described in this paper follows on from the TAMBIS project [13] in which queries written over the GRAIL description logic (DL) were mapped into execution plans in CPL Kleisli ....

....8] However, few such proposals have provided truly declarative query interfaces or high levels of transparency. The work described in this paper follows on from the TAMBIS project [13] in which queries written over the GRAIL description logic (DL) were mapped into execution plans in CPL Kleisli [8]. Limitations of the online TAMBIS query processor (http: img.cs.man.ac.uk tambis ) include: i) the ontology is represented using a relatively inexpressive DL, in which certain features of the biological domain are difficult to express; ii) the mapping between concepts in the ontology and ....

S.B. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1(1):36--53, Nov 1997.

....and retrieve it is relatively small. Most of the work in computer science directed to biological data has been in the area of heterogeneous databases, focusing on the semi structured nature of much of the data that makes it very difficult to store usefully in commercial relational databases [6]. Some work has begun in applying the work on wrappers and mediators to biological databases, for example TAMBIS [31] These systems 19 Figure 8: Overview of gene expression processing organization differ from ours in that they are pure implementations of wrapper mediator technology that are ....

S. B. Davidson and et al. Biokleisli:a digital library for biomedical researchers. Intnl. J. on Digital Libraries, 1(1):36--53, 1997.

.... in which data from various data sources are converted, merged, and stored in a centralized DBMS, e.g. Integrated Genomic Database (IGD) 32] and SRS [5] Middleware approaches, in which data are combined from multiple sources without creating a physical warehouse, e.g. BioKleisli [10], TAMBIS [1] and DiscoveryLink [16] etc. Due to the popularity of the Web, many online biological databases provide services through the Web and establish hyperlinks between related information in di#erent data sources. Migrating all relevant 23 data to a data warehouse allows for great ....

....whether the wrappers can be easily constructed for new data sources and easily modified for changes to the wrapped data sources. We surveyed three of the most widely used biological data integration systems: BioKleisli, SRS and DiscoveryLink based on the three criteria. The drivers in BioKleisli [10] system are equivalent to the wrappers. BioKleisli o#ers collection programming language (CPL) to construct a driver. CPL allows for the expression of complex transformation across heterogeneous databases. Sequence Retrieval System (SRS) 5] is an indexed flat file system built on the model of a ....

Susan B. Davidson, G. Christian Overton, Val Tannen, and Limsoon Wong. Biokleisli: A digital library for biomedical researchers. International Journal on Digital Libraries, 1(1):36--53, 1997.

....other applications. Searching genome databases is a difficult problem for a number of reasons: i) There is an explosive growth in the size of genome databases. ii) These databases are also distributed, requiring that meaningful data collections be identified before exhaustive queries are posed [16]. iii) The similarity measures are complex. Therefore, CPU and memory demands of these databases slow them down considerably for long queries. For example, comparing a mouse DNA sequence against the entire human genome database can take days with currently available search tools. There is a need ....

S. Davidson, G. Overton, V. Tannen, and L. Wong. BioKleisli: A digital library for biomedical researchers. Int. J. on Digital Libraries, 1(1):36-53, April 1997.

....and maintained in isolation from each other, and thus manifest classical syntactic and semantic heterogeneities. As a result, there has been considerable attention devoted to the development of proposals that ease the task of exploring or accessing heterogeneous bioinformatics resources (e.g. [9, 6, 7]) However, few such proposals have provided truly declarative query interfaces or high levels of transparency. The work described in this paper follows on from the TAMBIS project [12] in which queries written over the GRAIL description logic (DL) were mapped into execution plans in CPL Kleisli ....

....However, few such proposals have provided truly declarative query interfaces or high levels of transparency. The work described in this paper follows on from the TAMBIS project [12] in which queries written over the GRAIL description logic (DL) were mapped into execution plans in CPL Kleisli [7]. Limitations of the online TAMBIS query processor (http: img.cs.man.ac.uk tambis ) include: i) the ontology is represented using a relatively inexpressive DL, in which certain features of the biological domain are difficult to express; ii) the mapping between concepts in the ontology and ....

S.B. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1(1):36--53, Nov 1997.

....by navigation style. Although SRS is successful at providing navigational access between diverse resources, it provides limited facilities to support querying or programming over diverse sources. Several proposals have been made in these directions. In terms of query oriented access, BioKleisli [9] provides both a query language for ranging over data types described using a rich hierarchical data model and a collection of wrappers (known in Kleisli as drivers) for accessing biological resources. However, BioKleisli has no global schema providing a model of the available data, and thus can ....

....is one of the few systems to offer wrapper services together with a query language that is flexible enough to cope with bioinformatics resources. The output from the TAMBIS system is a query plan written in CPL [6] using a modified version of the BioKleisli library of biological database wrappers [9]. CPL (Collection Programming Language) allows the concise expression of retrieval requests over collections of data, with data types for representing arbitrarily nested sets, bags, lists, records and variants. An example CPL query, which retrieves all motifs in guppy proteins, is as follows: m ....

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S.B. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1(1):36--53, Nov 1997.

....over the contents of the warehoused data. Our approach is based on mediation as will be described in the next section. Several systems have been designed for domain specific integration of biomolecular data, providing nonmaterialized views of biological data sources. They include BioKleisli [DOTW97, BCD 98] and its extensions K2 [DCB 01] and Pizzkell Kleisli [Won00] the TINet multi database system based on the Object Protocol Model (OPM) and its Object Web Wrapper [EKL01, Lac00] DiscoveryLink [HKR 00] an extension for life sciences of DataJoiner and DB2 [Cha98] merged with ....

S. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1997.

....and retrieve it is relatively small. Most of the work in computer science directed to biological data has been in the area of heterogeneous databases, focusing on the semi structured nature of much of the data that makes it very difficult to store usefully in commercial relational databases [5]. Some work has begun in applying the work on wrappers and mediators to biological databases, for example TAMBIS [20] These systems differ from ours in that they are pure implementations of wrapper mediator technology that are centralized, do not allow for dynamic changes in sources, support ....

S. B. Davidson and et al. Biokleisli:a digital library for biomedical researchers. Intnl. J. on Digital Libraries, 1(1):36--53, 1997.

....and retrieve it is relatively small. Most of the work in computer science directed to biological data has been in the area of heterogeneous databases, focusing on the semi structured nature of much of the data that makes it very difficult to store usefully in commercial relational databases [6]. Some work has begun in applying the work on wrappers and mediators to biological databases, for example TAMBIS [25] These systems differ from ours in that they are pure implementations of wrapper mediator technology that are centralized, do not allow for dynamic changes in sources, support ....

S. B. Davidson and et al. Biokleisli:a digital library for biomedical researchers. Intnl. J. on Digital Libraries, 1(1):36--53, 1997.

....with it. It is the values of these molecular properties that determine which molecule is actually represented by the image on the screen. The properties specifiable are name, type, state and associated details, location, comments, and associated BioKRIS (Kleisli Related Integration Software) [3, 4] and other remote database queries. Each molecule is automatically provided with a unique name upon creation, which the user may alter as desired. Each molecule must also have a type specified. This type is based upon the underlying type database (see Section 3) and determines what the molecule ....

Davidson S., Overton C., Tannen V. & Wong L., "BioKleisli: A Digital Library for Biomedical Researchers". International Journal of Digital

....enough to accommodate a wide degree of heterogeneity at the data sources, and at the same time, represent the class structure evident from the taxonomic character of the data. To accommodate this, we use an object oriented formalism, but unlike the collection based model used by Bio Kleisi [DOTW97] we use F logic that is well equipped to represent object orientation, flexible enough to represent semistructured data, and has the machinery to perform inferences and recursive computation such as path expressions and transitive closure. # The computation of numeric aggregates and numeric ....

S. B. Davidson, G. C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Intl. Journal on Digital Libraries, 1(1):36--53, 1997.

....by supplying additional keywords to search Medline, modifying the nodes and edges of the pathway diagram, or exporting the extracted results into an interaction database. 3 3 Implementation The architecture of the PIES is shown in Figure 4. The main components are the Kleisli Query System[2, 3, 19], which accepts the user s input and performs the downloading of appropriate Medline abstracts and various transformations on the interaction database corresponding the various manipulation commands from the user. The BioNLP module[13] analyses the Medline abstracts to extract from them protein ....

....identical to that supported by Entrez[12] The last type of input is the more interesting one, since it means the PIES has to search Medline via the Entrez website for abstracts satisfying the specification. This download step is performed by the Kleisli Query System. The Kleisli Query System [2, 3, 19] is an advanced broad scale integration technology that has proved useful in the bioinformatics arena [1, 10] Many bioinformatics problems require access to data sources that are high in volume, highly heterogeneous and complex, constantly evolving, and geographically dispersed. Solutions to ....

S. Davidson et. al. BioKleisli: A digital library for biomedical researchers. International Journal of Digital Libraries, 1(1):36--53, 1997.

....on the comprehension syntax. Kleisli is itself implemented using the functional language SML. This paper describes the influence of functional programming research that benefits the Kleisli system, especially the less obvious ones at the implementation level. 1 Introduction The Kleisli system [14] is an advanced broad scale integration technology that has proved useful in the bioinformatics arena. Many bioinformatics problems require access to data sources that are high in volume, highly heterogeneous and complex, constantly evolving, and geographically dispersed. Solutions to these ....

....of CPL in Subsection 2.3. 2. 1 Architecture CPL Kleisli pipe memory shared Net Servers Remote GSDB GenBank GDB NCBI BLAST Sybase ASN.1 Drivers BLAST CPL Type NRC Optimizer Driver Object Complex Manager OPM Manager Library Primitive Module ACeDB The Kleisli system[14] is written entirely in SML NJ. The architecture of the system is depicted in the figure above. Kleisli is extensible in many ways: It can be used to support many other high level query languages by replacing the CPL module. Kleisli can also be used to support many different types of external data ....

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S. Davidson et. al. BioKleisli: A digital library for biomedical researchers. Int. J. Digital Libraries, 1(1):36--53, 1997.

....However, in TAMBIS, the user does not have to choose the sources, select the key words with which to filter the proteins, identify the location of the sources, express requests in the language of the source, or transfer data items between sources. Other systems, such as SRS [10] Bio Kleisli [8] and OPM [6] integrate multiple bioinformatics sources, but do so less transparently. All have the integration and reconciliation of some aspects of heterogeneity in common. However, they still leave the user to choose sources, the attributes to be used, and the order of query sub components in ....

....query language. This should allow remote access to a large number of databanks and analysis programs, along with a rudimentary query facility. The output from the TAMBIS system is a query plan written in CPL [5] using a modified version of the BioKleisli library of biological database wrappers [8]. CPL (Collection Programming Language) allows the concise expression of retrieval requests over collections of data, with data types for representing arbitrarily nested sets, bags, lists, records and variants. An example CPL query, which retrieves all motifs in guppy proteins, is as follows: m ....

[Article contains additional citation context not shown here]

S.B. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1(1):36--53, Nov 1997.

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Davidson, S., Overton, C., Tannen, V. & Wong, L. (1997), `BioKleisli: A digital library for biomedical researchers', International Journal of Digital Libraries 1(1), 36--53.

....has been to create a large number of di#erent databases, all in di#erent formats, typically using non standard data query software, and only really properly accessible to bioinformatics experts [3] So it is a big challenge to use these pieces together to answer new questions in biology. Kleisli [7] is an integration technology that is rather suitable in the bioinformatics arena. Many bioinformatics problems (1) require access to data sources that are highly heterogeneous, geographically distributed, highly complex, constantly evolving, and high in volume; 2) require solutions that involve ....

Davidson, S., Overton, C., Tannen, V., and Wong, L., BioKleisli: A digital library for biomedical researchers, International Journal of Digital Libraries, 1(1):36--53, 1997.

....data management systems to an easily extensible system that performs complex transformations on autonomous data sources that are heterogeneous and geographically dispersed. This paper describes some implementation details and example applications of Kleisli. 1 Introduction The Kleisli system [14, 32, 33] is an advanced broad scale integration technology that has proven very useful in the bioinformatics arena. Many bioinformatics problems require access to data sources that are large, highly heterogeneous and complex, constantly evolving, and geographically dispersed. Solutions to these problems ....

....7 A DOE Impossible Query Having seen the optimizations for queries that involve relational database sources, we now show a sample bioinformatics query that benefits significantly from these optimizations. In fact, it is the very first bioinformatics query implemented in Kleisli in 1994 [14], and was one of the so called impossible queries of a US Department of Energy Bioinformatics Summit Report (www.gdb.org Dan DOE whitepaper contents.html. The query was to find for each gene located on a particular cytogenetic band of a particular human chromosome as many of its non human ....

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S. Davidson et al. BioKleisli: A digital library for biomedical researchers. International Journal of Digital Libraries, 1(1):36--53, 1997.

....that draw pedigree diagrams perfectly. We are intrigued by their remarks and decide to explore the problem of building a system for the automatic layout of pedigree diagrams. We have at our command three general and powerful packages developed for previous applications: the Kleisli Query System [2, 3] developed for writing ad hoc queries over heterogeneous complex data sources that we can use for manipulation of large pedigree databases; the Graphviz package [4, 5] developed for automatic layout and drawing of directed graphs that we can adapt for drawing pedigree diagrams; and the ....

....and flexible self describing exchange format. The format consist of a lexical layer and a logical layer. The logical layer provides for the following data structuring concepts: sets, bags, lists, records, and variants which corresponds to the data types supported by the Kleisli Query System [2, 3]. The lexical layer specifies how data corresponding to these structural concepts are layout in a data stream. The important property of the lexical layer is that each data structuring concept is given an unambiguous encoding. As a result, the data items can be parsed without reference to any ....

[Article contains additional citation context not shown here]

Susan Davidson, Christian Overton, Val Tannen, and Limsoon Wong. BioKleisli: A digital library for biomedical researchers. International Journal of Digital Libraries, 1(1):36--53, April 1997.

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S. Davidson et al. BioKleisli: A digital library for biomedical researchers. Intl. J. Digit. Lib., 1:36--53, 1997.

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S. Davidson, C. Overton, V. Tannen, and L. Wong, "BioKleisli: A digital library for biomedical researchers," J. Digital Libraries, 1997.

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S. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1997.

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S.B. Davidson, C. Overton, V. Tannen, and L. Wong. BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries, 1(1):36--53, Nov 1997.

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Davidson, S.B., Overton,C., Tannen, V., and Wong, L. Bio-Kleisli: a digital library for biomedical researchers. 1997 Int. J. Digit. Libraries, 1, 36-53.

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S. Davidson et. al. BioKleisli: A digital library for biomedical researchers. International Journal of Digital Libraries, 1#1#:36#53, 1997.

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) Davidson, S. B., Overton, C., Tannen, V., and Wong, L.: BioKleisli: A Digital Library for Biomedical Researchers, J. Digital Libraries, Vol. 1, No. 1 (1996).

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