The advent of the Information Age and global connectivity has placed ethics center stage in the use of Information and Communication Technologies (ICT). As the drive towards the establishment of a socalled IT profession gains momentum, ethical conduct and codes of ethics have recently been formulated and introduced formally. Initiatives in this regard can be attributed to, among others, the ACM and the IEEE. Of particular significance is the ImpactCS Project commissioned by the joint taskforce of the ACM and IEEE, and funded by the USA's National Science Foundation. The increased globalization and inherent nature of ICT transcend physical and cultural borders, making it increasingly difficult to enforce accepted laws, regulations, and codes of conduct. It is thus the responsibility of Computer Science and Information Systems instructors to teach and instill professional values and ethical analysis skills in each and every student. Therefore, we investigate some issues pertaining to the teaching of computer ethics. We conclude this paper by presenting a possible framework to be used in the teaching of computer ethics, and apply this framework to our own institution.

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Next-generation sequencing technologies have redefined the way genome sequencing is performed. They are able to produce tens of millions of short sequences (reads), during a single experiment, and with a much lower cost than previously possible. Due to the dramatic increase in the amount of data generated, a challenging task is to map (align) a set of reads to a reference genome. In this paper, we study a different version of this problem: mapping these reads to a dynamically changing genomic sequence. We propose a new practical algorithm, which employs a suitable data structure that takes into account potential dynamic effects (replacements, insertions, deletions) on the genomic sequence. The presented experimental results demonstrate that the proposed approach can be extended and applied to address the problem of mapping short reads to multiple related genomes.

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