Department of Biochemistry and The Milner Therapeutics Institute, University of Cambridge, Cambridge, UK.
The Francis Crick Institute, Molecular Biology of Metabolism laboratory, London, UK.
Nat Methods. 2020 Jan;17(1):41-44. doi: 10.1038/s41592-019-0638-x. Epub 2019 Nov 25.
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.
我们提出了一个易于使用的集成软件套件 DIA-NN，该套件利用深度神经网络和新的定量和信号校正策略，用于处理数据非依赖采集（DIA）蛋白质组学实验。DIA-NN 提高了传统 DIA 蛋白质组学应用中的鉴定和定量性能，对于高通量应用特别有益，因为它速度快，并且当与快速色谱方法结合使用时，能够实现深度和可靠的蛋白质组覆盖。
