AUTOMATED BIOLOGICAL MASS SPECTROMETRY

摘要

Through cloud-based technologies of serverless processing, containers, distributed storage, and dynamic resource allocation [molecular and biological data processing] mass spectrometry data processing pipelines are created.These pipelines automatically start stop, execute, and scale directly to mass spectrometry data.Traditionally bioinformatics mass spectrometry data processing and analysis has been performed on a single computer.The data continues to grow in size which leads to increases in processing time and reaching single computer limits.This creates processing bottlenecks because a single computer has limited resources of CPU, memory, and disk space.Bioinformatics data processing can include processing of mass spectrometry data, genetic sequencing data, Mass spectrometry data processing has been traditionally performed as series or pipeline of algorithms where the output of one algorithm is the input to another.Different algorithms have different dependencies and even OS requirements causing integration issues.Passing data between the algorithms creates bottlenecks as the data itself often has to be transformed into a database or moved to a central location.