Collaborative Research: EAGER: Exploring beyond visualization: Data sonification of bacterial chemotaxis patterns

在这个大数据时代，以前所未有的速度收集信息，使研究人员无法以有意义的方式处理数据。在过去的三十年中，将数字流转换为图形表示已被证明对识别复杂数据集（如天气模式、股票市场波动和流感流行）的趋势非常有用。虽然可视化是一种强大的数据分析方法，但并非所有数据都适用于可视化。将信息映射到声音，是一种从视觉混乱数据中提取有用信息的替代方法。一个熟悉的数据声化的例子是盖革计数器，它将不可见的伽马辐射转换为可听到的咔哒声频率。这个项目展示了超声波在研究微生物如何游向对其生存至关重要的营养物质中的效用。目标是促进更广泛地使用超声来分析生物研究界的大数据。数据的声音化还可以提高公众的科学素养和公众对科学技术的参与。正如朗朗上口的希格斯玻色子曲调所证明的那样，经过处理的数据使亚原子粒子的发现更容易为公众所接受。在这个项目中，声音和音乐被用来提供一种媒介，通过这种媒介，以一种欢迎的方式吸引小学生对科学的兴奋。另一个值得注意的方面是，数据声化提供了一个方便的平台，让视障人士参与研究。该项目汇集了生物系统工程和数字音乐作曲方面的专业知识，为交叉训练的学生研究助理提供了不同的视角。在这个项目中，超声波被用来检测暴露于化学刺激（即趋化性）后微生物游泳模式的变化。当用显微镜观察一群游动的微生物时，它们的运动看起来很混乱，使得个体生物运动路径的细微变化无法实时识别。通过将视觉图像实时映射到频域，可以将混乱的视觉运动转化为听觉声音的可识别差异。具体的项目目标是：(1)识别在超声数据中检测到的细菌游动运动的特征；(2)优化视频显微镜设置和视频滤波器，提高采集数据的信噪比；(3)实时对数据进行声音处理，以便同时向观察者输入音频和视频；(4)评估具有不同游动行为的细菌的数据超声算法的鲁棒性；(5)筛选超出训练集的微生物的趋化性，以评估超声过程的成功。这项工作的一个成果将是一个与视觉观察同步的实时生成超声数据的平台，以允许在一定浓度范围内高通量筛选不同物种对不同化学效应物的趋化反应。另一个可能更有影响力的结果是，将显著扩展生物科学家可以使用的工具，以识别他们收集的复杂数据中的模式。该奖项由系统和合成生物学集群以及分子和细胞生物学部门的细胞和动力学集群共同资助。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。

In this Era of Big Data an unprecedented amount of information is being collected at rates that are overwhelming researchers' capacity to process data in meaningful ways. Converting streams of numbers into graphical representations has proven to be useful over the past three decades to identify trends in complex data sets such as weather patterns, stock market fluctuations, and flu epidemics. While visualization is a powerful approach to data analysis, not all data are amenable to visualization. Sonification, the mapping of information to sound, is an alternative method for extracting useful information from visually chaotic data. One familiar example of data sonification is a Geiger counter that converts invisible gamma radiation to an audible frequency of clicks. This project demonstrates the utility of sonification in a study of how microbes swim toward nutrients that are critical for their survival. The goal is to promote more widespread use of sonification to analyze big data within the biological research community. Sonification of data can also increase public scientific literacy and public engagement with science and technology. As demonstrated by the catchy Higgs Boson tune, sonified data made the discovery of subatomic particles more accessible to the public. Sound and music are used in this project to provide a medium through which to engage elementary school-age children in a welcoming manner about the excitement of science. Another notable aspect is that data sonification provides a convenient platform to engage sight-impaired individuals in research. The project brings together expertise in biological systems engineering and digital music composition that provide diverse perspectives for cross-training student research assistants.In this project sonification is used to detect changes in the swimming patterns of microorganisms upon exposure to a chemical stimulus (i.e. chemotaxis). When examining a population of swimming microbes through a microscope the movement appears chaotic, making subtle changes in the paths of individual organisms impossible to discern in real time. By mapping visual images to the frequency domain in real-time one can transform the chaotic visual motion to discernible differences in auditory sounds. The specific project objectives are to: (1) identify the features of bacterial swimming motion that are detected in sonified data; (2) optimize video microscopy settings and video filters to enhance the signal-to-noise ratio of the data collected; (3) sonify data in real time to allow simultaneous audio and visual input to an observer; (4) evaluate the robustness of data sonification algorithms for bacteria that have different swimming behaviors; and (5) screen microbes for chemotaxis beyond the training set to evaluate the success of the sonification process. One outcome of this work will be a platform to generate sonified data in real-time that is synchronous with visual observations to allow high-throughput screening of chemotactic responses for various species to different chemoeffectors over a range of concentrations. Another, and perhaps more impactful outcome, will be to significantly expand the tools that biological scientists have at their disposal to identify patterns in complex data that they collect.This award is jointly funded by the Systems and Synthetic Biology Cluster and the Cellular and Dynamics Cluster in the Division of Molecular and Cellular Biology.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.