Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data

Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data

Abstract Background Mass spectrometry is an important experimental technique in the field of proteomics. However, analysis of certain mass spectrometry data faces a combination of two challenges: first, even a single experiment produces a large amount of multi-dimensional raw data and, second, signa...

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Bibliographic Details
Main Authors: Konstantin Bob, David Teschner, Thomas Kemmer, David Gomez-Zepeda, Stefan Tenzer, Bertil Schmidt, Andreas Hildebrandt
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Bioinformatics
Subjects:
Mass spectrometry
Locality-sensitive hashing
Signal processing
Online Access:https://doi.org/10.1186/s12859-022-04833-5

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