Selecting oligonucleotide probes for whole-genome tiling arrays with a cross-hybridization potential.

For designing oligonucleotide tiling arrays popular, current methods still rely on simple criteria like Hamming distance or longest common factors, neglecting base stacking effects which strongly contribute to binding energies. Consequently, probes are often prone to cross-hybridization which reduces the signal-to-noise ratio and complicates downstream analysis. We propose the first computationally efficient method using hybridization energy to identify specific oligonucleotide probes. Our Cross-Hybridization Potential (CHP) is computed with a Nearest Neighbor Alignment, which efficiently estimates a lower bound for the Gibbs free energy of the duplex formed by two DNA sequences of bounded length. It is derived from our simplified reformulation of t-gap insertion-deletion-like metrics. The computations are accelerated by a filter using weighted ungapped q-grams to arrive at seeds. The computation of the CHP is implemented in our software OSProbes, available under the GPL, which computes sets of viable probe candidates. The user can choose a trade-off between running time and quality of probes selected. We obtain very favorable results in comparison with prior approaches with respect to specificity and sensitivity for cross-hybridization and genome coverage with high-specificity probes. The combination of OSProbes and our Tileomatic method, which computes optimal tiling paths from candidate sets, yields globally optimal tiling arrays, balancing probe distance, hybridization conditions, and uniqueness of hybridization

Processamento de dados em Zynq APSoC

Mestrado em Engenharia de Computadores e TelemáticaField-Programmable Gate Arrays (FPGAs) were invented by Xilinx in 1985, i.e. less than 30 years ago. The influence of FPGAs on many directions in engineering is growing continuously and rapidly. There are many reasons for such progress and the most important are the inherent reconfigurability of FPGAs and relatively cheap development cost. Recent field-configurable micro-chips combine the capabilities of software and hardware by incorporating multi-core processors and reconfigurable logic enabling the development of highly optimized computational systems for a vast variety of practical applications, including high-performance computing, data, signal and image processing, embedded systems, and many others. In this context, the main goals of the thesis are to study the new micro-chips, namely the Zynq-7000 family and to apply them to two selected case studies: data sort and Hamming weight calculation for long vectors.Field-Programmable Gate Arrays (FPGAs) foram inventadas pela Xilinx em 1985, ou seja, há menos de 30 anos. A influência das FPGAs está a crescer continua e rapidamente em muitos ramos de engenharia. Há varias razões para esta evolução, as mais importantes são a sua capacidade de reconfiguração inerente e os baixos custos de desenvolvimento. Os micro-chips mais recentes baseados em FPGAs combinam capacidades de software e hardware através da incorporação de processadores multi-core e lógica reconfigurável permitindo o desenvolvimento de sistemas computacionais altamente otimizados para uma grande variedade de aplicações práticas, incluindo computação de alto desempenho, processamento de dados, de sinal e imagem, sistemas embutidos, e muitos outros. Neste contexto, este trabalho tem como o objetivo principal estudar estes novos micro-chips, nomeadamente a família Zynq-7000, para encontrar as melhores formas de potenciar as vantagens deste sistema usando casos de estudo como ordenação de dados e cálculo do peso de Hamming para vetores longos