Data Set Used
BACKGROUND Accumulation of nitrated protein is seen in peripheral lung and cells from patients with chronic obstructive pulmonary disease (COPD). Nitrated protein causes abnormal protein function, but the nitration was believed to be an irreversible process. However, there are accumulating evidences that this process is reversible by an active denitration… (More)
Patient record data are potentially highly sensitive and their secondary use raises both ethical and data protection issues. Disclosure of patient data could cause serious difficulties for the medical profession and be potentially damaging for individual patients and clinicians. Yet at the same time patient records are a hugely valuable resource in terms of… (More)
Advances in data storage, data collection and inference techniques have enabled the creation of huge databases of personal information. Dissemination of information from such databases-even if formally anonymised, creates a serious threat to individual privacy through statistical disclosure. One of the key methods developed to limit statistical disclosure… (More)
As genomic data becomes widely used, the problem of genomic data privacy becomes a hot interdisciplinary research topic among geneticists, bioinformaticians and security and privacy experts. Practical attacks have been identified on genomic data, and thus break the privacy expectations of individuals who contribute their genomic data to medical research, or… (More)
Protecting data privacy and anonymity requires a better understanding of the conditions and mechanisms under which they may be threatened.
SUMMARY: The human brain is organized into large-scale functional modules that have been shown to evolve in childhood and adolescence. However, it remains unknown whether structural brain networks are similarly refined during development, potentially allowing for improvements in executive function. In a sample of 882 participants (ages 8-22) who underwent… (More)
The assessment of statistical disclosure risk often requires the linking of data. There are effective means of linking data for simple scenarios; but it is not clear how best to approach linkage for more complex scenarios. We examine linkage approaches for three simple scenarios and argue that they might be combined.
This paper explains a potential approach to synthetic data generation using genetic algorithms. It based on the principle that optimisation can be strong, accurate and efficient if there is sufficient prior knowledge of solution space. This approach is applicable because its evolutionary and competitive process compares different synthetic versions of the… (More)