Reason: Confidential due to business interest. Please email rdm@lboro.ac.uk for more information.
Information management applied to bioinformatics. Appendices B, C, and D.
dataset
posted on 2019-08-16, 08:00authored byHiten Vyas
Appendix B.
Stakeholder identification
Exercise:
•
Raw interview data from stakeholder identification.
•
Analysis of the interviews with potential stakeholders.
Appendix C:
Raw interview data from Sanger Institute case study.
Appendix D:
Raw interview data from AstraZeneca case study
Abstract:
Bioinformatics, the discipline concerned with biological information management
is essential in the post-genome era, where the complexity of data processing allows
for contemporaneous multi level research including that at the genome level,
transcriptome level, proteome level, the metabolome level, and the integration of
these -omic studies towards gaining an understanding of biology at the systems
level. This research is also having a major impact on disease research and drug
discovery, particularly through pharmacogenomics studies.
In this study innovative resources have been generated via the use of two case
studies. One was of the Research & Development Genetics (RDG) department at
AstraZeneca, Alderley Park and the other was of the Pharmacogenomics Group at
the Sanger Institute in Cambridge UK. In the AstraZeneca case study senior
scientists were interviewed using semi-structured interviews to determine
information behaviour through the study scientific workflows. Document analysis
was used to generate an understanding of the underpinning concepts and fonned
one of the sources of context-dependent information on which the interview
questions were based. The objectives of the Sanger Institute case study were
slightly different as interviews were carried out with eight scientists together with
the use of participation observation, to collect data to develop a database standard
for one process of their Pharmacogenomics workflow.
The results indicated that AstraZeneca would benefit through upgrading their data
management solutions in the laboratory and by development of resources for the
storage of data from larger scale projects such as whole genome scans. These
studies will also generate very large amounts of data and the analysis of these will
require more sophisticated statistical methods. At the Sanger Institute a minimum
information standard was reported for the manual design of primers and included in
a decision making tree developed for Polymerase Chain Reactions (PCRs). This
tree also illustrates problems that can be encountered when designing primers along
with procedures that can be taken to address such issues