Algorithmic challenges in population scale genomics

点击翻译按钮获取中文摘要

This proposal aims to address some of the algorithmic challenges offered by data explosion through high throughput sequencing technologies. We aim to bridge the gap between the capacity to generate data, which is growing faster than the Moore's Law, and the ability to manage, store, communicate and analyze it, through novel algorithmic approaches. Typically our algorithmic approaches rely on combinatorial optimization, data structures, approximation algorithms and techniques from combinatorial pattern matching. We will aim to develop novel methods aiming to simultaneously compress and index genome sequence data through re-ordering reads coming from high throughput sequencing platforms on which existing compression and mapping technologies will be applied. This boosting technique for is motivated by the Locally Consistent Parsing technique, which is applied the first time to genomics in this proposal.