Deep correction of DNA sequencing errors by data mining algorithms

本计画的目的是研究数TB的基因组序列资料中的多层错误修正问题，并借由新颖的资料探勘演算法来解决这些问题。高通量测序平台产生了大量有用的原始数据，但也产生了广泛的错误。新算法能够纠正更深层的错误，以进一步提高数据质量。预期成果包括基因组数据产业的知识进步以及生物技术和数据挖掘之间的跨学科合作。这也为法医学和个性化医疗中需要准确基因组信息的基因组决策提供了显着的好处。

This project aims to investigate the many layers of error correction problems in the terabytes of genomic sequence data, and aims to solve these problems by novel data mining algorithms. High-throughput sequencing platforms have generated massive amounts of useful raw data, but also made widespread errors. The new algorithms are capable of correcting errors at deeper layers to further enhance data quality. Expected outcome includes the knowledge advancement of genomic data industry and interdisciplinary collaboration between biotechnology and data mining. This also provides significant benefit for genomic decisions in forensics and personalised medicine which demand accurate genomic information.