Predicting dependencies using domain-based coupling

Software dependencies play a vital role in programme comprehension, change impact analysis and other software maintenance activities. Traditionally, these activities are supported by source code analysis; however, the source code is sometimes inaccessible or difficult to analyse, as in hybrid systems composed of source code in multiple languages using various paradigms (e.g. object-oriented programming and relational databases). Moreover, not all stakeholders have adequate knowledge to perform such analyses. For example, non-technical domain experts and consultants raise most maintenance requests; however, they cannot predict the cost and impact of the requested changes without the support of the developers. We propose a novel approach to predicting software dependencies by exploiting the coupling present in domain-level information. Our approach is independent of the software implementation; hence, it can be used to approximate architectural dependencies without access to the source code or the database. As such, it can be applied to hybrid systems with heterogeneous source code or legacy systems with missing source code. In addition, this approach is based solely on information visible and understandable to domain users; therefore, it can be efficiently used by domain experts without the support of software developers. We evaluate our approach with a case study on a large-scale enterprise system, in which we demonstrate how up to 65 of the source code dependencies and 77% of the database dependencies are predicted solely based on domain information.

Defining new criteria for selection of cell-based intestinal models using publicly available databases

The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies.

Can level of education, accreditation and use of databases in cardiac rehabilitation be improved? Results from the European Cardiac Rehabilitation Inventory Survey

Professional skills, education and accreditation, along with clinical outcome assessment, are considered important factors to achieve comprehensive delivery and quality of cardiac rehabilitation (CR). This study assessed professional educational programmes, accreditation and use of databases in CR across the European countries.

Bioinformatics tools and databases for the study of human growth hormone

Advances in novel molecular biological diagnostic methods are changing the way of diagnosis and study of metabolic disorders like growth hormone deficiency. Faster sequencing and genotyping methods require strong bioinformatics tools to make sense of the vast amount of data generated by modern laboratories. Advances in genome sequencing and computational power to analyze the whole genome sequences will guide the diagnostics of future. In this chapter, an overview of some basic bioinformatics resources that are needed to study metabolic disorders are reviewed and some examples of bioinformatics analysis of human growth hormone gene, protein and structure are provided.