Towards a 'Big Data Browser' for standardised datasets in neuroscience, and its application in ion channel and single cell modelling.

在过去的十年里，大数据以及复杂、多方面、公开可用的数据集已经进入了现代神经科学研究。然而，与其他领域不同，神经科学中的数据集非常异构，通常需要大量的后处理和上下文注释。这种元数据的丰富本身就提出了一个挑战，因为任何数据都需要根据不断变化的情况需求进行过滤和可视化，并且它们的高维性通常使这些数据集难以驾驭，难以使用传统的静态可视化技术。在初步工作（提交）中，我们已经手动注释，丰富和标准化了2000多个离子通道模型的数据集，根据其已发布的上下文和对预定义测试协议的常规响应。然后，我们开发了一个“大数据浏览器”，允许用户快速浏览所有离子通道模型，并通过交互式过滤可视化其功能特征。这些离子通道模型已经成为创建实验约束的神经元和网络模型领域的标准。我们的方法为用户搜索特定的离子通道类型提供了所有必要的信息，以缩小候选模型的范围，并且可以节省单个研究人员多达4周的初步文献研究和测试模拟。分为三个工作包，我们的目标是在离子通道模型的背景下维护和扩展此资源，并使其成为神经科学数据的通用案例浏览器。在WPI中，我们计划将数据库扩展为独立于模拟器并包含实验数据，使其更加全面，并允许将实验与模型进行直接比较。这将使该资源成为理论家和实验家的有用工具。接下来，我们计划将我们的数据库与其他神经科学资源整合，并在一个全面和最新的平台上维护这些资源。在WPII中，我们的目标是扩展数据库的现有功能，包括多通道动力学、多房室模型，并最终将这两者联合收割机结合起来，以允许分析复杂的动力学。我们将使用在试点工作和WPI中开发的现有框架。我们的最终目标是产生一个工具，用于完整创建和测试具有复杂形态和通道组成的神经元模型。这将对实验约束建模大有好处，使模型的创建更容易，更直观。基于提出的离子通道功能障碍或形态畸变来验证功能缺陷的假设只需要几个小时，而不是几个星期。在WPIII中，我们的目标是将我们的离子通道模型数据浏览器扩展到神经科学的其他领域，使其成为通用的“大数据浏览器”。目前大数据的主要问题是创建图形界面，允许在不需要专业知识的情况下探索复杂的数据集。我们希望为这些数据集的存储、组织和可视化创建一个统一的界面，以使数据更容易访问和重用。最终的结果将是一个开箱即用的数据可视化器，可以适应任何新的数据集，甚至允许以简单的方式比较数据集之间。总之，我们的建议将为该领域提供一个资源，用于构建具有复杂离子通道动力学的详细神经元模型，并将其直接与实验进行比较。第二步，它还将为该领域提供一个急需的数据接口，适用于任何数据集，解决如何有效地共享和比较大量注释的大数据集的全领域问题。

Big data, and with it complex, multifaceted, publicly available data sets, has arrived in modern neuroscience research over the last decade. Unlike other fields however, the datasets in neuroscience are very heterogeneous and often require heavy post-processing and contextual annotation. This enrichment of metadata presents a challenge in itself because any data needs to be filtered and visualised with changing situational requirements, and their high dimensionality often make these data sets unruly and difficult for traditional static visualisation techniques. In preliminary work (submitted), we have manually annotated, enriched and standardised a dataset of over 2000 ion channel models according to their published context and their stereotypical response to predefined test protocol. We then developed a ``big data browser'' to allow users to quickly browse all ion channel models and visualise their functional characteristics with interactive filtering. These ion channel models have become the standard in the field for creating experimentally-constrained neuron and network models. Our method provides all necessary information for users searching for specific ion channel types to narrow down the circle of candidate models and can save an individual researcher as much as 4 weeks of preliminary literature research and test simulations.In this proposal, we aim to expand our work. Divided into three work packages, we aim to maintain and expand this resource in the context of ion channel models, as well as to make it a general case browser for neuroscience data. In WPI, we plan to expand the database to be simulator-independent and to include experimental data, making it more comprehensive and allow direct comparison of experiments to models. This will make the resource a useful tool for theorists as well as experimentalists. Next, we plan to integrate our database with other neuroscience resources, and maintain this all in one comprehensive and up-to-date platform. In this way, we can take advantage of existing frameworks and act as a complement to them.In WPII, we aim to expand the current functionality of the database to include multi-channel dynamics, multi-compartmental models, and finally to combine these two together to allow for analysis of complex dynamics. We will use the existing framework developed in our pilot work and WPI. Our ultimate goal is to produce a tool for the complete creation and testing of neuron models with complex morphology and channel composition. This will be of great benefit to experimentally-constrained modelling, making the creation of models easier and more intuitive. Testing a hypothesis of functional deficits based on proposed ion channel disfunction or morphological aberration will only take a matter of hours instead of several weeks.In WPIII, we aim to expand our data browser for ion channel models to other areas in neuroscience by making it a general 'Big Data Browser'. The main issue with big data currently is to create graphical interfaces that allow the exploration of complex datasets without requiring expert knowledge. We hope to create a unified interface for the storage, organisation and visualisation of datasets such as these, in order to make data more accessible and reusable. The end result will be an out-of-the-box data visualiser that can be adapted to any new dataset, and even to allow the comparison between datasets in an easy way.In summary, our proposal will provide the field with a resource for building detailed neuron models with complex ion channel dynamics and comparing them directly to experiments. In a second step, it will also provide the field with a much-needed data interface, adaptable to any dataset, solving a field-wide problem of how to efficiently share and compare heavily annotated big data sets.