A Flow Trace Generator using Graph-based Traffic Classification Techniques

We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.

An Evaluation of Compression Schemes for Wireless Networks

Data gathering, either for event recognition or for monitoring applications is the primary intention for sensor network deployments. In many cases, data is acquired periodically and autonomously, and simply logged onto secondary storage (e.g. flash memory) either for delayed offline analysis or for on demand burst transfer. Moreover, operational data such as connectivity information, node and network state is typically kept as well. Naturally, measurement and/or connectivity logging comes at a cost. Space for doing so is limited. Finding a good representative model for the data and providing clever coding of information, thus data compression, may be a means to use the available space to its best. In this paper, we explore the design space for data compression for wireless sensor and mesh networks by profiling common, publicly available algorithms. Several goals such as a low overhead in terms of utilized memory and compression time as well as a decent compression ratio have to be well balanced in order to find a simple, yet effective compression scheme.

RNA editing in kinetoplastids

RNA editing in kinetoplastid protozoa is a post-transcriptional process of uridine insertion or deletion in mitochondrial mRNAs. The process involves two RNA species, the pre-edited mRNA and in most cases a trans-acting guide RNA (gRNA). Sequences within gRNAs define the position and extend of mRNA editing. Both mRNAs and gRNAs are encoded by mitochondrial genes in the kinetoplast DNA (kDNA), which consists of thousands of small circular DNA molecules, called minicircles, encoding thousands of gRNAs, catenated together and with a few mRNA encoding larger circles, the maxicircles, to form a huge DNA network. Editing has been shown to result in translatable mRNAs of bona fide mitochondrial genes as well as novel alternatively edited transcripts that are involved in the maintenance of the kDNA itself. RNA editing occurs within large protein-RNA complexes, editosomes, containing gRNA, preedited and partially edited mRNAs and also structural and catalytically active proteins. Editosomes are diverse in both RNA and protein composition and undergoe structural remodeling during the maturation. The compositional and structural diversity of editosomes further underscores the complexity of the RNA editing process.

The Trypanosoma brucei MitoCarta and its regulation and splicing pattern during development

It has long been known that trypanosomes regulate mitochondrial biogenesis during the life cycle of the parasite; however, the mitochondrial protein inventory (MitoCarta) and its regulation remain unknown. We present a novel computational method for genome-wide prediction of mitochondrial proteins using a support vector machine-based classifier with approximately 90% prediction accuracy. Using this method, we predicted the mitochondrial localization of 468 proteins with high confidence and have experimentally verified the localization of a subset of these proteins. We then applied a recently developed parallel sequencing technology to determine the expression profiles and the splicing patterns of a total of 1065 predicted MitoCarta transcripts during the development of the parasite, and showed that 435 of the transcripts significantly changed their expressions while 630 remain unchanged in any of the three life stages analyzed. Furthermore, we identified 298 alternatively splicing events, a small subset of which could lead to dual localization of the corresponding proteins.