Limits...
A perspective for biomedical data integration: design of databases for flow cytometry.

Drakos J, Karakantza M, Zoumbos NC, Lakoumentas J, Nikiforidis GC, Sakellaropoulos GC - BMC Bioinformatics (2008)

Bottom Line: The proposed schema can potentially achieve up to 8 orders of magnitude reduction in query complexity and up to 2 orders of magnitude reduction in response time for data originating from flow cytometers that record 256 colours.This is mainly achieved by managing to maintain an almost constant number of data-mining procedures regardless of the size and complexity of the stored information.Analysis of the requirements of a specific domain for integration and massive data processing can provide the necessary schema modifications that will unlock the additional functionality of a relational database.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr

ABSTRACT

Background: The integration of biomedical information is essential for tackling medical problems. We describe a data model in the domain of flow cytometry (FC) allowing for massive management, analysis and integration with other laboratory and clinical information. The paper is concerned with the proper translation of the Flow Cytometry Standard (FCS) into a relational database schema, in a way that facilitates end users at either doing research on FC or studying specific cases of patients undergone FC analysis

Results: The proposed database schema provides integration of data originating from diverse acquisition settings, organized in a way that allows syntactically simple queries that provide results significantly faster than the conventional implementations of the FCS standard. The proposed schema can potentially achieve up to 8 orders of magnitude reduction in query complexity and up to 2 orders of magnitude reduction in response time for data originating from flow cytometers that record 256 colours. This is mainly achieved by managing to maintain an almost constant number of data-mining procedures regardless of the size and complexity of the stored information.

Conclusion: It is evident that using single-file data storage standards for the design of databases without any structural transformations significantly limits the flexibility of databases. Analysis of the requirements of a specific domain for integration and massive data processing can provide the necessary schema modifications that will unlock the additional functionality of a relational database.

Show MeSH

Related in: MedlinePlus

The proposed database schema. The proposed schema consists of three tables. Under this schema, data acquired on every HIL is useful, without the need for extra data-mining actions. For example, all measurements of antigen CD20 are stored in a unique field (e.g. 'Unified Name 2').
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2267440&req=5

Figure 5: The proposed database schema. The proposed schema consists of three tables. Under this schema, data acquired on every HIL is useful, without the need for extra data-mining actions. For example, all measurements of antigen CD20 are stored in a unique field (e.g. 'Unified Name 2').

Mentions: The database schema we propose (Figure 5) is able to fulfil these requirements because of its clear horizontal structure. During our extensive testing, no query or HIL of any level contained data requiring further processing to become meaningful.


A perspective for biomedical data integration: design of databases for flow cytometry.

Drakos J, Karakantza M, Zoumbos NC, Lakoumentas J, Nikiforidis GC, Sakellaropoulos GC - BMC Bioinformatics (2008)

The proposed database schema. The proposed schema consists of three tables. Under this schema, data acquired on every HIL is useful, without the need for extra data-mining actions. For example, all measurements of antigen CD20 are stored in a unique field (e.g. 'Unified Name 2').
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2267440&req=5

Figure 5: The proposed database schema. The proposed schema consists of three tables. Under this schema, data acquired on every HIL is useful, without the need for extra data-mining actions. For example, all measurements of antigen CD20 are stored in a unique field (e.g. 'Unified Name 2').
Mentions: The database schema we propose (Figure 5) is able to fulfil these requirements because of its clear horizontal structure. During our extensive testing, no query or HIL of any level contained data requiring further processing to become meaningful.

Bottom Line: The proposed schema can potentially achieve up to 8 orders of magnitude reduction in query complexity and up to 2 orders of magnitude reduction in response time for data originating from flow cytometers that record 256 colours.This is mainly achieved by managing to maintain an almost constant number of data-mining procedures regardless of the size and complexity of the stored information.Analysis of the requirements of a specific domain for integration and massive data processing can provide the necessary schema modifications that will unlock the additional functionality of a relational database.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr

ABSTRACT

Background: The integration of biomedical information is essential for tackling medical problems. We describe a data model in the domain of flow cytometry (FC) allowing for massive management, analysis and integration with other laboratory and clinical information. The paper is concerned with the proper translation of the Flow Cytometry Standard (FCS) into a relational database schema, in a way that facilitates end users at either doing research on FC or studying specific cases of patients undergone FC analysis

Results: The proposed database schema provides integration of data originating from diverse acquisition settings, organized in a way that allows syntactically simple queries that provide results significantly faster than the conventional implementations of the FCS standard. The proposed schema can potentially achieve up to 8 orders of magnitude reduction in query complexity and up to 2 orders of magnitude reduction in response time for data originating from flow cytometers that record 256 colours. This is mainly achieved by managing to maintain an almost constant number of data-mining procedures regardless of the size and complexity of the stored information.

Conclusion: It is evident that using single-file data storage standards for the design of databases without any structural transformations significantly limits the flexibility of databases. Analysis of the requirements of a specific domain for integration and massive data processing can provide the necessary schema modifications that will unlock the additional functionality of a relational database.

Show MeSH
Related in: MedlinePlus