Data_Sheet_4_A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation.zip

Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.

精准的分子浓度（molecular concentrations）对于生化网络的可靠分析以及分子生物学与系统生物学预测模型的构建至关重要，然而此类模型所采用的蛋白质与代谢物浓度数据往往约束性不足，且难以复现。使用多源数据时面临的挑战包括命名规则与计量单位的冲突，以及实验流程、数据处理及模型实施方面的差异。为获得蛋白质与代谢物水平的一致性估计值，我们整合并标准化了多源数据，以计算校正后分子浓度（Adjusted Molecular Concentrations）。我们发现，众多分子物种在不同脑区与细胞类型中具有高度的可复现性与一致性，这与严格的稳态调控机制相符。我们通过与神经退行性疾病、脑区及细胞类型相关的蛋白质差异表达分析，验证了该标准化方法的应用价值。我们还将该结果应用于脑能量代谢的概念验证模拟实验中。标准化脑分子图谱（Brain Molecular Atlas）克服了数据缺失或不一致的障碍，可为系统生物学研究提供支撑，并作为生物分子建模的资源库对外开放。