Objectives
Graduates of the Specialist Certificate in Clinical Research (Informatics and Analysis) will:
* Have an understanding of privacy, ethical, intellectual property issues as they relate to Clinical Trials and Bioinformatics research
* Have an understanding of basic Database models and terminology. (e.g. relational databases, tables, columns and rows, normalization, joins), including simple queries using SQL, and techniques for the extraction of data from a database for analysis in other tools (e.g. Excel, SPSS, SAS)
* Have an appreciation of "federated" data models such as the MMIM project, and their use in multi-institution, cross-disciplinary studies, including advantages and disadvantages
* Have an understanding of issues relating to research data including ownership, data quality and design of data collection mechanisms, linking of data from multiple resdearch sources, linkage to Victorian and Australian public health databases, and techniques for de-identification of data
* Have an appreciation of the types and volumes of data that will be generated by new techniques in clinical research (e.g. genomic data, proteomic data)
* Gain a basic understanding of data mining techniques, their applicability to Clinical Research and their limitations, e.g. neural networks, genetic algorithms, clustering and optimisation techniques
* Become familiar with the current trends in Bioinformatics and how these relate to clinical research, e.g. the world-wide HAPMAP project
* Gain an understanding of the complexity and basic techniques used in analysis of pharmaco-genetic data, such as analysis of SNPs and associated haplotypes, familial linkages and so on
* Have a working knowledge of the major publicly available medical, genetic and biological databases on the internet (e.g. GenBank, Swiss-Prot, OMIM, etc.)
* Have an appreciation of the variety of public software for use in specific Bioinformatics research (e.g. various versions of BLAST, MFOLD, etc.)
* Understand the other professionals that are involved in Clinical Research, and gain an appreciation of when and who to ask for specialist assistance (e.g. statisticians and other mathematical experts, database experts and general computing staff)
