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Data quality assurance and quality control measures in large multicenter stroke trials: the African-American Antiplatelet Stroke Prevention Study experience: ... trial. In addition to standard data quality control ...

DeJuran Richardson et al.

Current Controlled Trials in Cardiovascular Medicine , 2001

Progress in Establishing Common Standards for Exchanging Proteomics Data: The Second Meeting of the HUPO Proteomics Standards Initiative: ... ASTM mass spectrometry standard and the data model for a proteomics ...

Sandra Orchard et al.

Comparative and Functional Genomics , 01 Apr 2003

ScanImage: Flexible software for operating laser scanning microscopes: ... are achieved through standard data acquisition boards. The ...

Thomas A Pologruto et al.

BioMedical Engineering OnLine , 17 May 2003

Evaluation and validation issues in the development of transgenic mouse carcinogenicity bioassays.: ... bioassay results as the standard. The data also suggest that the ...

R W Tennant

Environmental Health Perspectives , 01 Apr 1998

Bioinformatics process management: information flow via a computational journal: ... from libraries with standard data models to elaborate ...

Lance Feagan et al.

Source Code for Biology and Medicine , 03 Dec 2007

GAIA: a gram-based interaction analysis tool – an approach for identifying interacting domains in yeast: ... tested against a gold-standard data set and achieves a true ...

Kelvin X Zhang et al.

BMC Bioinformatics , 30 Jan 2009

Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatment: ... lack a universal standard. Results A three-parameter lognormal distribution model was tested on over 300 sets of microarray data. The model treats the ...

Tomokazu Konishi

BMC Bioinformatics , 13 Jan 2004

Evaluating concentration estimation errors in ELISA microarray experiments: ... assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. ...

Don Simone Daly et al.

BMC Bioinformatics , 26 Jan 2005

AlzPharm: integration of neurodegeneration data using RDF: ... RDF Schema (RDFS), as a standard data model to facilitate ...

Hugo YK Lam et al.

BMC Bioinformatics , 09 May 2007

An Integrated Korean Biodiversity and Genetic Information Retrieval System: ... format as its metadata standard for data exchange. Data quality ...

Jeongheui Lim et al.

BMC Bioinformatics , 12 Dec 2008

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