A rich analytical environment for flow cytometry experimental results.

Siebert, Janet; Cios, Krzysztof J; Newell, M Karen

Siebert, Janet; Cios, Krzysztof J; Newell, M Karen.

Affiliation

Siebert J; Department of Computer Science and Engineering, University of Colorado at Denver and Health Sciences Center, Campus Box 109, P.O. Box 173364, Denver, CO 80217-3364, USA. jsiebert@acm.org

Int J Bioinform Res Appl ; 2(1): 52-62, 2006.

Article in En | MEDLINE | ID: mdl-18048153

ABSTRACT

Existing analysis tools for flow cytometry data offer specialised but limited functionality. This work presents advantages of combining the cytometer's data with sample-specific information. Data is loaded into a relational database, where the analyst can query based on sample characteristics such as species, gender, diet type or sample stain type.

Subject(s)

Computational Biology/methods; Flow Cytometry/methods; Anemia, Sickle Cell/metabolism; Equipment Design; HIV/metabolism; Humans; Immunologic Techniques; Information Storage and Retrieval; Lipids/chemistry; Membrane Microdomains; Neoplasms/metabolism; Programming Languages; Spectrometry, Fluorescence/methods; User-Computer Interface

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Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Flow Cytometry Limits: Humans Language: En Journal: Int J Bioinform Res Appl Journal subject: INFORMATICA MEDICA Year: 2006 Document type: Article Affiliation country: United States Country of publication: Switzerland

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