Signal Processing and Applied Machine Learning for the Detection of Nucleic Acids

使用基于dna的解决方案快速检测微生物对社会治疗疾病具有积极而深远的影响。不幸的是，目前基于dna的方法是昂贵的，不可移植的，并且需要经过技术培训的操作人员。这些挑战可以从三个不同的角度来解决：(i)改进和开发新的检测化学；（ii）引入新的工程解决方案（例如基于半导体的化学成像设备）；（iii）开发信号处理和机器学习算法，以便从数据中提取尽可能多的信息。该项目的主要目标集中在后者：解决信号处理、机器学习和数据科学的作用，以增强基于dna的医疗保健问题解决方案。这类问题的例子包括：检测病原体，量化病原体存在的数量，以及在单一化学反应中检测多种病原体。目标是使用从标准仪器、最先进仪器获得的数据来触及这些问题，然后处理从基于半导体的化学成像设备获得的新数据。虽然这项工作的新颖性在于开发从数据中提取信息的新算法（从基于dna的实验中获得），但这个项目的好处本质上延伸到那些增强检测化学和开发新的工程解决方案。研究方向：人工智能技术、数字信号处理、数学生物学

The rapid detection of microorganisms using DNA-based solutions has positive, far-reaching consequences on society for curing diseases. Unfortunately, current DNA-based methods are expensive, non-portable and require a technically trained operator. These challenges can be tackled from three different angles: (i) improving and developing novel detection chemistries; (ii) introducing new engineering solutions (such as semiconductor-based chemical imaging devices); and (iii) developing signal processing and machine learning algorithms in order to extract as much information from the data as possible. The primary aim of this project focuses on the latter: addressing the role of signal processing, machine learning and data science for enhancing DNA-based solutions for problems in healthcare. Examples of such problems include: detecting pathogens, quantifying how much of a pathogen exists, and detecting multiple pathogens in a single chemical reaction. The goal is to touch on these issues using data obtained from: standard instruments, state-of-the-art instruments, and then tackling new data obtained from semiconductor-based chemical imaging devices. Although the novelty of this work lies in developing new algorithms for extracting information from data (obtained from DNA-based experiments), the benefits of this project inherently extend to those enhancing detection chemistries and developing new engineering solutions.Research AreasArtificial intelligence technologies, Digital signal processing and Mathematical Biology