ABI Innovation: Synthetic Sequence Designs for Real Biology

石溪大学（Stony Brook University）获得了一笔赠款，用于统一、推广和扩展合成生物学的算法设计技术，这些技术在试点研究中已被证明是有用的，并将其转化为一套连贯的工具，以解决微生物学中的重要实验问题。该项目将产生算法和软件工具，将富有想象力的序列设计与几个领域的DNA合成结合起来。特别是，他们将提高鲁棒性，效率和通用的新方法，以确定关键的DNA或RNA序列信号的位置。这项工作将大规模合成与采用组合组测试和平衡格雷码的复杂设计结合起来。软件工具将被部署，以使技术的广泛传播，并改进一项利用精心设计的序列合成的新技术（采用组合学的思想，即德布鲁因序列），以在全基因组范围内测定转录因子。这也将涉及优化这类合成序列所需的算法研究，以及评估这些设计有效性的实验工作。基于阵列的寡核苷酸合成技术提供了数千种低成本、定制设计的序列变体。为各种编码序列的大规模设计而开发的算法将使研究人员能够利用基于阵列的合成技术并分析其性能。最后，合成基因组学的出现意味着实验室菌株可以被“重构”，即重新设计，使它们更容易在实验中操作。该项目将建立在限制性位点放置算法的基础上，以产生一个可在网络上访问的基因组分解工具。计算科学和生命科学研究人员之间的合作，通过组合算法和离散优化方面的新算法结果，以及基因表达、转录因子分析和序列信号检测方面的基础发现，推动了这两个学科的发展。该项目将产生软件和实验工具，以推进分子生物学的广泛领域。除了本研究的算法贡献之外，他们还将开发普遍感兴趣的实验室材料。教育成果包括指导本科生研究生。该项目的软件和结果可从网站http://www.cs.sunysb.edu/~skiena/dna获得。

A grant has been awarded to Stony Brook University to unify, generalize, and expand algorithmic design techniques for synthetic biology, which have proven useful in pilot studies, into a coherent set of tools to address important experimental problems in microbiology. The project will result in algorithmic and software tools to couple imaginative sequence design with DNA synthesis in several areas. In particular, they will improve the robustness, efficiency, and generality of a new approach to identify the locations of critical DNA or RNA sequence signals. This work couples large-scale synthesis with sophisticated designs employing combinatorial group testing and balanced Gray codes. Software tools will be deployed to enable broad dissemination of the technology and improve a new technique exploiting the synthesis of carefully-designed sequences (employing ideas from combinatorics, namely de Bruijn sequences) to titrate transcription factors on a genome-wide scale. This will also address algorithmic research necessary to optimize this class of synthetic sequences, coupled with experimental work to evaluate the efficacy of these designs. Array-based oligo synthesis technologies provide access to thousands of low-cost, custom-designed sequence variants. The algorithms developed for the large-scale design of diverse coding sequences will allow researchers to exploit array-based synthesis technologies and assay their performance. Finally, the advent of synthetic genomics means that laboratory strains can be "refactored", i.e., redesigned to make them easier to experimentally manipulate. The project will build on restriction-site placement algorithms to produce a web-accessible genome factorization tool.This collaboration between computational and life sciences researchers advances both disciplines, through new algorithmic results in combinatorial algorithms and discrete optimization as well as fundamental discoveries regarding gene expression, transcription factor analysis, and sequence signal detection. The project will result in software and experimental tools to advance broad areas of molecular biology. Beyond the algorithmic contributions of this research, they will develop laboratory materials of general interest. Educational outcomes include mentoring of undergraduate research students. Software and results of this project will be available from the website http://www.cs.sunysb.edu/~skiena/dna.