III: Small: RUI: Designing Structure-Phenotype Query-Retrieval and Analysis Systems for Microscopy-Based Whole Organism Studies

信息学和生命科学交叉领域的一个新兴挑战是由研究中产生的数据构成的，这些研究涉及分析分子探针在全系统生物水平上的影响。这些复杂的数据包括两个不同的组成部分：分子的结构描述和被研究生物体表现出的表型反应的图像或视频记录。这类（结构-表型）数据越来越多地出现在基础科学和应用科学中，涉及范围广泛的研究活动，从旨在了解基因在模式生物中的功能作用的研究到寻求发现对抗疾病的新药的研究。然而，缺乏最先进的方法和系统来集成存储和分析这种结构-表型数据。本研究将通过设计基于内容的表示、存储、查询和分析结构表现型信息的算法和系统来解决这个问题。特别是，在生成结构表型数据的基础问题和转化问题上工作的科学家将能够在单一框架内查询和推理信息，这是目前不存在的。根据该合同开发的方法和系统将通过与领域专家的合作进行验证。此外，这些系统将公开提供。最后，该项目将吸引和培养学生在计算机科学、生物学和化学的界面上工作，重点是扩大本科生和研究生的参与，并让公众参与高质量的学习体验。该项目将进行综合研究、教育和推广计划，以发展结构表现型（SP）数据管理和分析领域，包括结构表示、图像分析、查询检索和与共轭SP数据相关的信息分析的算法技术。利用SP数据进行推理在生物化学科学中日益变得至关重要，并在了解生命基础以及开发/改进疾病治疗方法方面发挥着重要作用。从计算机科学的角度来看，SP数据由复杂的多维实体组成，这些实体对表示、检索、建模和分析技术的有效和高效设计提出了关键挑战。本建议所设想的研究将在三个重点下调查一系列相互关联的问题：(1)设计结构-表型数据的稳健表示技术；(2)开发统一的索引方法，以支持基于内容的结构和表型数据的查询检索；(3)设计分析来自整个生物体显微镜研究的结构-表型数据的技术，以及为重点生物领域和数据集建立公开可用的概念验证系统。作为本次调查的一部分，所开发的技术、系统和结果将在领域专家的合作下进行测试和验证。该提案的教育部分包括旨在吸引妇女和代表性不足的少数民族学生并为其提供密集指导的活动。最后，该计划还包括课程开发，以教育学生了解SP数据分析，并让公众参与高质量的学习体验。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

An emerging challenge at the intersection of informatics and life sciences is constituted by data generated from studies that involve analyzing the effect of molecular probes at a system-wide organism level. This complex data comprises two distinct components: structural description of molecules and image or video-based record of phenotypic responses exhibited by the organism(s) being studied. Such (structure-phenotype) data is increasingly being generated in both basic and applied sciences across a wide spectrum of research activities ranging from those that aim to understand the functional role of genes in model organisms to studies that seek to discover new drugs against diseases. There is however, a singular lack of methods and systems at the state-of-the-art which allow integrated storage and analysis of such structure-phenotype data. This research will address this problem by designing algorithms and systems for content-based representation, storage, querying, and analysis of structure-phenotype information. In particular, scientists working on both basic and translational problems where structure-phenotype data is generated will be able to query and reason with the information within a single framework the likes of which currently do not exist. The methods and systems developed under this award will be validated through collaborations with domain specialists. Furthermore, these systems will be made publicly available. Finally, this project will attract and train students to work at the interface of computer science, biology, and chemistry, with a focus on broadening participation both at the undergraduate and graduate levels and engage public audiences in high-quality learning experiences.This project will pursue an integrated research, educational, and outreach program to develop the area of structure-phenotype (SP) data management and analysis encompassing algorithmic techniques in structure representation, image analysis, query-retrieval, and analysis of information related to conjugated SP data. Reasoning with SP data is increasingly becoming critical in bio-chemical sciences and plays an important role in understanding the basis of life as well as in development/improvement of therapeutics against diseases. From the computer science perspective, SP data consists of complex, multidimensional entities which present critical challenges for effective and efficient design of representation, retrieval, modeling, and analysis techniques. The research envisaged in this proposal will investigate a series of interrelated problems, under three foci: (1) Designing techniques for robust representation of structure-phenotype data, (2) Development of a unified indexing approach to support content-based query-retrieval of structural and phenotypic data, and (3) Designing techniques for analysis of structure-phenotype data from whole-organism microscopy studies as well as building publicly available proof-of-concept systems for focused biological domains and data-sets. The techniques, systems, and results developed as part of this investigation will be tested and verified in collaboration with domain specialists. The educational component of the proposal includes activities aimed at attraction and intensive mentoring of women and underrepresented minority students. Finally, the plan includes curriculum development to educate students about SP data analysis and engaging public audiences in high-quality learning experiences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.