Hasselt University licenses SAS® Scientific Discovery Solutions

including SAS® Microarray and SAS® Proteomics, for Research and Education programmes

SAS, the leader in business intelligence, announced that Hasselt University (Limburg, Belgium) has licensed SAS® Scientific Discovery Solution, a comprehensive platform that enables scientific research organizations to speed-up and streamline their research data analysis.
The SAS® Scientific Discovery Solution is composed of SAS® Research Data Management, the centralized data and analytical process repository and three analytical modules; SAS® Microarray, SAS® Genetic Marker and SAS® Proteomics, which enable statistical analysis and visualization of microarray, genetics and proteomics data respectively.

Hasselt University was established in 1971 and consists of three faculties: the Faculty of Medicine, the Faculty of Sciences, and the Faculty of Applied Economy. Moreover, the University Hasselt joins forces with the University of Maastricht (The Netherlands), resulting in a joint initiative called the transnational University Limburg (tUL). Within the Faculty of Sciences, there are study programmes in Mathematics, Physics, Computer Science, Chemistry and Biology. On the research side, the Center for Statistics (“CenStat”) has been established in 1998 to unify teaching, research and consulting activities in theoretical and applied statistics at the University Hasselt. The scientific research conducted within the center, headed by Professor Geert Molenberghs, is internationally renowned, both for its theoretical as well as for its applied content. The international postgraduate programs “Master of Science in Biostatistics” and “Master of Science in Applied Statistics” and consultancy records are well known also. Statistical consultancy is provided to both public scientific research organizations and pharmaceutical companies.

SAS® Scientific Discovery Solutions will be used within research and education at CenStat for both its applied and theoretical statistical components. Professor Tomasz Burzykowski and his colleagues are conducting research in bioinformatics data analysis (including microarray and proteomics data). CenStat’s staff members have many years of expertise in developing analytic routines in SAS and they have co-authored several books and papers on linear mixed models using SAS(*).

“SAS® Scientific Discovery modules offer a comprehensive tool allowing for the storage, processing and analysis of genomic and proteomic data”, said Professor Burzykowski at CenStat “The availability of the modules offers various advantages to CenStat. First, since SAS is utilized extensively by the members and students at CenStat, inclusion of SAS® Scientific Discovery in the statistical software toolbox is a natural step. Second, analysis of genomic and proteomic data becomes a rapidly developing area of research at CenStat. From this point of view, the modules increase CenStat’s research potential. Finally, their availability is also important for our teaching activities. We plan to make them available, e.g., to the students following the courses on genetic data analysis and bioinformatics within our Master in Biostatistics program. “

“We are happy to have University of Hasselt within our scientific discovery user base. Also we are pleased that our software is being used in the Masters program. The University will provide us with useful feedback that we can then plug into the solution. The user community is important to us”, said Dr. Mark Lambrecht, Life Sciences Consultant at SAS Belgium.

Related links:
SAS solutions for the pharmaceutical market

(*)References:

• Simplified Hierarchical Linear Models for the Evaluation of Surrogate Endpoints. Tibaldi et al. (Journal of Statistical Computation and Simulation) 2003.
• Verbeke, Geert and Molenberghs, Geert (Eds.) (1997) Linear Mixed Models in Practice (A SAS-Oriented Approach). Springer, N.Y.
• Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen.
  ISBN #: 1-59047-504-6 (2005) Analysis of Clinical Trials Using SAS: A Practical Guide.