Biomedical subjects

Robert Molidor

Publications and source records attributed to Robert Molidor.

3 recordsLinked to original sources

PubMed2005

MARS: microarray analysis, retrieval, and storage system.

BACKGROUND: Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. RESULTS: MARS (Microarray Analysis and Retrieval System) provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS), a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. CONCLUSION: We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

Algorithms↗

PubMed2005

Systems for the management of pharmacogenomic information.

Recent breakthroughs in biological research have been made possible by remarkable advances in high-performance computing and the establishment of a highly sophisticated information technology infrastructure. This chapter gives an overview of the main and most important technologies needed for the management of pharmacogenomic information, namely database management systems and software and hardware architectures. Because pharmacogenomics deals with a great many of public and/or proprietary data, the most prominent ways for easy storage, retrieval, analysis, and exchange are presented. Processing these data requires the use of sophisticated software architectures. Several most recent practices useful for a pharmacogenomic environment are explained. Multitiered application design and web services are discussed and described independent of the major enterprise development platforms. Because life sciences are becoming increasingly quantitative and because state-of-the-art software architectures use many system resources, this chapter presents the most recent and powerful systems for parallel data processing and data storage. Finally, shared and distributed memory systems and combinations of them as well as different storage architectures such as directly attached storage, network-attached storage, and storage-area network are explained in detail.

Animals↗

PubMed2003

New trends in bioinformatics: from genome sequence to personalized medicine.

Molecular medicine requires the integration and analysis of genomic, molecular, cellular, as well as clinical data and it thus offers a remarkable set of challenges to bioinformatics. Bioinformatics nowadays has an essential role both, in deciphering genomic, transcriptomic, and proteomic data generated by high-throughput experimental technologies, and in organizing information gathered from traditional biology and medicine. The evolution of bioinformatics, which started with sequence analysis and has led to high-throughput whole genome or transcriptome annotation today, is now going to be directed towards recently emerging areas of integrative and translational genomics, and ultimately personalized medicine.Therefore considerable efforts are required to provide the necessary infrastructure for high-performance computing, sophisticated algorithms, advanced data management capabilities, and-most importantly-well trained and educated personnel to design, maintain and use these environments. This review outlines the most promising trends in bioinformatics, which may play a major role in the pursuit of future biological discoveries and medical applications.

Computational Biology↗