CIF:Medium:Collaborative Research:An Information-theoretic approach to nanopore sequencing

CIF：中：合作研究：纳米孔测序的信息理论方法

• 批准号: 1703403
• 负责人: Sreeram Kannan
• 金额: $ 75万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1703403&HistoricalAwards=false
• 关键词: CIF; Medium; Collaborative; Research; Information

Fast and inexpensive DNA sequencing technology is beginning to impact society through applications ranging from personalized medicine to understanding of ecological systems enabled by second generation sequencers. Wider applicability of second-generation sequencing technology is limited, however, by the short length of the DNA fragments that can be read. Nanopore sequencing has the potential to overcome several shortcomings of state-of-the art short-read sequencing.The goal of this project is to create new foundational theory and algorithms enabling several applications of nanopore sequencing. This research will support nanopore technology to become a leading next-generation sequencing approach. This project also contains a unique inter-university education and research program, which will include joint and collaborative student advising and curricular development.To realize the advantages of nanopore sequencing, methods for reducing and combating sequencing errors need to be developed. In a nanopore sequencer, DNA is transmigrated through a nanopore, and the ion current variations through the pore are measured to infer the DNA sequence. The mapping from the DNA sequence to the observed current trace, has several impairments (causing errors) including multiple nucleotides affecting each observation, random variations in nanopore response, dwelling time variations, synchronization errors, and noise. This project develops a holistic approach using tools from information theory and bio-informatics based on multiple interacting thrusts: (1) developing mathematical models and (2) information theory for nanopore sequencing, (3) decoding algorithms exploiting the structure of the nanopore channel, and (4) the theory and methodology for applications in DNA forensics, DNA phasing and DNA information storage. We couple this with an existing experimental nanopore sequencing research program, guiding models and the theory/algorithms with specific data as well as validating these ideas.

快速、廉价的DNA测序技术正开始影响社会，其应用范围从个性化医疗到由第二代测序仪实现的对生态系统的理解。然而，由于可读取的DNA片段长度较短，限制了第二代测序技术的广泛适用性。纳米孔测序有潜力克服当前最先进的短读测序的几个缺点。该项目的目标是创造新的基础理论和算法，使纳米孔测序的几种应用成为可能。这项研究将支持纳米孔技术成为领先的下一代测序方法。该项目还包含一个独特的大学间教育和研究项目，包括联合和合作的学生咨询和课程开发。为了实现纳米孔测序的优势，需要开发减少和对抗测序误差的方法。在纳米孔测序仪中，DNA通过纳米孔迁移，并测量通过孔的离子电流变化来推断DNA序列。从DNA序列到观察到的电流轨迹的映射有几个缺陷（导致错误），包括影响每个观察的多个核苷酸、纳米孔响应的随机变化、停留时间变化、同步误差和噪声。该项目利用信息论和生物信息学的工具开发了一种基于多个相互作用的整体方法：(1)开发数学模型；(2)纳米孔测序的信息论；(3)利用纳米孔通道结构的解码算法；(4)应用于DNA取证、DNA分相和DNA信息存储的理论和方法。我们将此与现有的实验纳米孔测序研究计划结合起来，指导模型和具有特定数据的理论/算法，并验证这些想法。

项目成果

Learning in Gated Neural Networks

• 发表时间: 2019-06
• 作者: Ashok Vardhan Makkuva;Sewoong Oh;Sreeram Kannan;P. Viswanath

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation

• 发表时间: 2020-05
• 期刊: ArXiv
• 作者: A. Mondal;A. Bhattacharya;Sudipto Mukherjee;Sreeram Kannan;Himanshu Asnani;A. Prathosh

CCMI : Classifier based Conditional Mutual Information Estimation

• 发表时间: 2019-06
• 作者: Sudipto Mukherjee;Himanshu Asnani;Sreeram Kannan

Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms

• 发表时间: 2018-02
• 作者: Ashok Vardhan Makkuva;P. Viswanath;Sreeram Kannan;Sewoong Oh

Deepcode: Feedback Codes via Deep Learning

• DOI: 10.1109/jsait.2020.2986752
• 发表时间: 2018-07
• 期刊: IEEE Journal on Selected Areas in Information Theory
• 作者: Hyeji Kim;Yihan Jiang;Sreeram Kannan;Sewoong Oh;P. Viswanath