Remote streaming 3D visualisation platform for raw and analysed data from biological mass spectrometry repositories

生物学家越来越希望了解控制每一个生物体功能的基因、代谢物和蛋白质组成部分之间复杂的相互作用。系统生物学领域的出现是为了克服传统还原论方法的缺陷，传统还原论方法已经确定了构建块本身和许多个体相互作用，但无法推断这些块的系统如何一致行动和反应。系统生物学的应用是广泛的，因为它有望彻底改变我们对植物、动物和人类健康过程的理解，以及它们如何在疾病下分解以及如何避免这种分解。通常，系统生物学方法从一个特定生物样本的“快照”开始。质谱法是一种普遍的技术，用于获取样品中蛋白质或代谢物的快照，它通过电离样品，然后根据产生的电荷测量每种组成化合物的质量和数量。这通常不足以完全分离出样品，因此使用液相或气相色谱的前一相来提供初始分离。由于技术和生物学的变化，有必要对样品进行多次分析以获得可靠的读数。有趣的生物化学物质也可以被分解成具有特征的片段，并进行测量，这通常会对该生物化学物质进行自信的鉴定。所有这些都使系统生物学逐渐成为一门计算学科。然而，由于数据集变得如此之大，因此存在这样一种危险，即该过程变得越来越不透明，质谱从业者无法访问，因此更有可能被用作“黑匣子”。因此，至关重要的是提供工具和平台，允许专家用户通过检查获得的原始数据来验证、确认和解释结果，否则，处理过程中的偏差、错误和错误假设将经常被忽视。然而，庞大的数据集证明是一个挑战，因为现有的工具加载和处理可视化数据的速度很慢，这严重限制了生产力，并且由于内存有限，无法对整个实验进行综合比较。出现这种情况的部分原因是，现有的数据格式没有设计成能够简化感兴趣区域的检索，也没有设计成能够快速、有效地实现可视化所需的不同级别的细节。我们建议为标准投诉数据设计这样的表示，并从那里我们将首次演示来自本地存储的交互式3D可视化，而不会延迟。由于内存开销问题也得到了缓解，将整个实验的结果和原始数据集成在一起的新颖可视化方案将成为可能，极大地促进了质谱分析的质量控制、验证、确认和专家解释。此外，通过开发专门的图像压缩技术，我们将展示跨互联网的实时远程可视化，其方式类似于谷歌Earth，但首次扩展了质谱可视化的需求。位于剑桥Hinxton的欧洲生物信息学研究所最近通过ProteomeXchange联盟将原始数据存入他们的PRIDE公共数据存储库，该存储库存储了来自世界各地的大量公共资助实验。截至2012年9月，它拥有3.24亿个质谱。我们的远程可视化平台将展示通过在线出版物和网络资源链接的即时无缝原始数据访问的潜力，这将大大改善这些战略社区数据源的设施，可访问性和重用性。

Biologists are increasing wishing to understand the complex interactions between the building blocks of genes, metabolites and proteins that control the function of every living organism. The field of systems biology has emerged to overcome the deficiencies of the traditional reductionist approach, which has identified the building blocks themselves and many of the individual interactions but has not been able to deduce how systems of these blocks act and react in unison. The application of systems biology is widespread, as it promises to revolutionise our understanding of healthy processes in plants, animals and humans, as well as how they break down under disease and how this breakdown can be averted. Often the systems biology approach starts with a 'snapshot' of a particular biological sample. Mass spectrometry is a pervasive technique for gaining a snapshot of the proteins or metabolites in a sample, and it does this by ionising the sample and then measuring each constituent compound's mass and quantity based on the resulting charge. This is often not enough to separate out the sample fully and therefore a preceding phase of liquid or gas chromatography is used to provide an initial separation. Due to technical and biological variations, it will be necessary to analyse the sample a number of times to get reliable readings. Interesting biochemicals can also be broken up into characteristic fragments and these measured, which often gives a confident identification of that biochemical. All this has led systems biology to become a progressively computational discipline. Since the datasets are becoming so large, however, that there is a danger that the process becomes more and more opaque and inaccessible to mass spectrometry practitioners and so more likely to be used as a 'black box'. It is therefore vitally important that tools and platforms are available that allow expert user verification, validation and interpretation of results by checking the raw data acquired, otherwise bias, errors and false assumptions in processing will be routinely overlooked. The massive datasets prove a challenge, however, as existing tools are slow to load and process the data for visualisation which severely limits productivity and precludes the integrated comparison of whole experiments due to limited memory. Part of the reason for this is that existing data formats have not been designed for streamlined retrieval of regions of interest or at varying levels of detail necessary for fast, efficient visualisation. We propose to design such a representation for standards-complaint data, and from that we will demonstrate interactive 3D visualisations from local storage for the first time without delay. Since memory overhead issues are also mitigated, novel visualisation schemes integrating results and raw data across complete experiments will be possible, greatly facilitating the quality control, verification, validation and expert interpretation of MS analyses.Furthermore, through development of specialised image compression, we will demonstrate real-time remote visualisation across the Internet, in a manner similar to Google Earth but for the first time extended for the demands of mass spectrometry visualisation. The European Bioinformatics Institute at Hinxton, Cambridge, has through the ProteomeXchange consortium recently launched raw data deposition into their PRIDE public data repositories, which stores vast amount of publically-funded experiments from around the world. As of September 2012, it holds 324 million mass spectra. Our remote visualisation platform will demonstrate the potential for immediate and seamless raw data access linked by online publications and web resources, which would lead to substantially improved facility, accessibility and re-use of these strategic community data sources.