PubMed Health⌕ Search

PubMed · 16597336

MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation.

Abstract

BACKGROUND: The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polymorphisms in DNA and genome-wide analysis of mRNA concentrations. Local array data management solutions are instrumental for efficient processing of the results and for subsequent uploading of data and annotations to a global certified data repository at the EBI (ArrayExpress) or the NCBI (GeneOmnibus). DESCRIPTION: To facilitate and accelerate annotation of high-throughput expression profiling experiments, the Microarray Information Management and Annotation System (MIMAS) was developed. The system is fully compliant with the Minimal Information About a Microarray Experiment (MIAME) convention. MIMAS provides life scientists with a highly flexible and focused GeneChip data storage and annotation platform essential for subsequent analysis and interpretation of experimental results with clustering and mining tools. The system software can be downloaded for academic use upon request. CONCLUSION: MIMAS implements a novel concept for nation-wide GeneChip data management whereby a network of facilities is centered on one data node directly connected to the European certified public microarray data repository located at the EBI. The solution proposed may serve as a prototype approach to array data management between research institutes organized in a consortium.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leandro Hermida, Olivier Schaad, Philippe Demougin, Patrick Descombes, Michael Primig. 2006-04-05. MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation.. https://doi.org/10.1186/1471-2105-7-190

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Creating a medical English-Swedish dictionary using interactive word alignment.

BACKGROUND: This paper reports on a parallel collection of rubrics from the medical terminology systems ICD-10, ICF, MeSH, NCSP and KSH97-P and its use for semi-automatic creation of an English-Swedish dictionary of medical terminology. The methods presented are relevant for many other West European language pairs than English-Swedish. METHODS: The medical terminology systems were collected in electronic format in both English and Swedish and the rubrics were extracted in parallel language pairs. Initially, interactive word alignment was used to create training data from a sample. Then the training data were utilised in automatic word alignment in order to generate candidate term pairs. The last step was manual verification of the term pair candidates. RESULTS: A dictionary of 31,000 verified entries has been created in less than three man weeks, thus with considerably less time and effort needed compared to a manual approach, and without compromising quality. As a side effect of our work we found 40 different translation problems in the terminology systems and these results indicate the power of the method for finding inconsistencies in terminology translations. We also report on some factors that may contribute to making the process of dictionary creation with similar tools even more expedient. Finally, the contribution is discussed in relation to other ongoing efforts in constructing medical lexicons for non-English languages. CONCLUSION: In three man weeks we were able to produce a medical English-Swedish dictionary consisting of 31,000 entries and also found hidden translation errors in the utilized medical terminology systems.

Database Management Systems↗

Validation of the Provincial Transfer Authorization Centre database: a comprehensive database containing records of all inter-facility patient transfers in the province of Ontario.

BACKGROUND: The Provincial Transfer Authorization Centre (PTAC) was established as a part of the emergency response in Ontario, Canada to the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003. Prior to 2003, data relating to inter-facility patient transfers were not collected in a systematic manner. Then, in an emergency setting, a comprehensive database with a complex data collection process was established. For the first time in Ontario, population-based data for patient movement between healthcare facilities for a population of twelve million are available. The PTAC database stores all patient transfer data in a large database. There are few population-based patient transfer databases and the PTAC database is believed to be the largest example to house this novel dataset. A patient transfer database has also never been validated. This paper presents the validation of the PTAC database. METHODS: A random sample of 100 patient inter-facility transfer records was compared to the corresponding institutional patient records from the sending healthcare facilities. Measures of agreement, including sensitivity, were calculated for the 12 common data variables. RESULTS: Of the 100 randomly selected patient transfer records, 95 (95%) of the corresponding institutional patient records were located. Data variables in the categories patient demographics, facility identification and timing of transfer and reason and urgency of transfer had strong agreement levels. The 10 most commonly used data variables had accuracy rates that ranged from 85.3% to 100% and error rates ranging from 0 to 12.6%. These same variables had sensitivity values ranging from 0.87 to 1.0. CONCLUSION: The very high level of agreement between institutional patient records and the PTAC data for fields compared in this study supports the validity of the PTAC database. For the first time, a population-based patient transfer database has been established. Although it was created during an emergency situation and data collection is dependent on front-line medical workers, the PTAC data has achieved a high level of validity, perhaps even higher than many purpose built databases created during non-emergency settings.

Database Management Systems↗

Properties of a federated epidemiology query system.

PURPOSE: The purpose of the study was to establish knowledge about how online access to epidemiological data from general practitioners (GPs) electronic health record (EHR) system should be provided. Before such systems are developed and deployed a decision about the appropriate system architecture must be made. Such a decision should ideally be based on knowledge about the properties of different system architectures. This choice is important because the system architecture may affect the willingness of GPs to participate in providing epidemiological data from their EHR system. METHOD: Verifying the performance and properties of an architectural approach by implementing and deploying a system on a trans-institutional level and performing evaluations studies is a very resource demanding method to establish a foundation for the decision of appropriate system architecture. Instead, we have tried to create this foundation by constructing a prototype system, establish knowledge about the properties of the system using experiments, and finally compare the properties of the federated approach to the properties of the centralised approach. By using this methodological approach we provide the best available knowledge, on this stage, for the appropriate system architecture to use for providing access to epidemiological data from the local population. RESULTS: Our experimental results show that it is possible to improve the timeliness and the temporal and spatial resolution of epidemiological data, compared to traditional centralised disease surveillance systems. Up-to-date epidemiological data from the local population may be provided directly from the source EHR system within 4s. The responsiveness of the system is minimally affected (0.1s) as the number of participating data providers grows from 1 to 49 data providers. The comparison of the federated approach to the centralised approach indicates that federated approaches avoid the privacy issues involved, as intended; it offers better scalability when computing speed is compared, and it provides better specificity because more data about the patient may be used. CONCLUSION: The conclusion from our study is that the federated approach to providing epidemiological data about the local population has many benefits over the traditional centralised approach. A federated approach to an epidemiology system may raise the GPs awareness of local disease outbreak because it is possible to share information about incidence rates of communicable diseases and use of laboratory requests in a geographical area that predates laboratory-based disease surveillance. The effects of the federated approach could be improved data quality in the EHR systems and improved representativeness of the epidemiological data for the areas covered by such systems.

Database Management Systems↗