Analysis of security and privacy challenges for DNA-genomics applications and databases.

DNA technology is rapidly moving towards digitization. Scientists use software tools and applications for sequencing, synthesizing, analyzing and sharing of DNA and genomic data, operate lab equipment and store genetic information in shared datastores. Using cutting-edge computing methods and techniques, researchers have decoded human genome, created organisms with new capabilities, automated drug development and transformed food safety. Such software applications are typically developed to progress scientific understanding and as such cyber security is never a concern for these applications. However, with the increasing commercialisation of DNA technologies, coupled with the sensitivity of DNA data, there is a need to adopt a security-by-design approach. In this paper we investigate bio-cyber security threats to genomic-DNA data and software applications making use of such data to advance scientific research. Specifically, we adopt an empirical approach to analyse and identify vulnerabilities within genomic-DNA databases and bioinformatics software applications that can lead to cyber-attacks affecting the confidentiality, integrity and availability of such sensitive data. We present a detailed analysis of these threats and highlight potential protection mechanisms to help researchers pursue these research directions.

Epilepsy and intellectual disability: does epilepsy increase the likelihood of co-morbid psychopathology?

Although epilepsy is particularly common among people with intellectual disability (ID) it remains unclear whether it is associated with an increased likelihood of co-morbid psychopathology. We therefore investigated rates of mental health problems and other clinical characteristics in patients with ID and epilepsy (N = 156) as compared to patients with ID but no epilepsy (N = 596). All participants were consecutive referrals to specialist mental heath services. Specialist clinicians agreed on the mental health diagnoses by applying ICD-10 clinical criteria using information gained from interviews with key informants and the patients. Bivariate and multivariate analyses showed that patients with epilepsy were more likely to live in residential housing and have severe ID in line with previous evidence. However, the presence of epilepsy was not associated with an increased likelihood of co-morbid psychopathology. On the contrary, rates of mental health problems, including schizophrenia spectrum, personality and anxiety disorders, were significantly lower among patients with epilepsy. The results are discussed in the context of mood-stabilizing and other psychotropic effects of anti-epileptic drugs in adults with ID and epilepsy, as well as possible diagnostic overshadowing.

Mi-DISCOVERER: A bioinformatics tool for the detection of mi-RNA in human genome.

MicroRNAs (miRNAs) are 22 nucleotides non-coding RNAs that play pivotal regulatory roles in diverse organisms including the humans and are difficult to be identified due to lack of either sequence features or robust algorithms to efficiently identify. Therefore, we made a tool that is Mi-Discoverer for the detection of miRNAs in human genome. The tools used for the development of software are Microsoft Office Access 2003, the JDK version 1.6.0, BioJava version 1.0, and the NetBeans IDE version 6.0. All already made miRNAs softwares were web based; so the advantage of our project was to make a desktop facility to the user for sequence alignment search with already identified miRNAs of human genome present in the database. The user can also insert and update the newly discovered human miRNA in the database. Mi-Discoverer, a bioinformatics tool successfully identifies human miRNAs based on multiple sequence alignment searches. It's a non redundant database containing a large collection of publicly available human miRNAs.