Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments.

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Bibliographic Details
Title: Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments.
Authors: Koss AR; Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, USA., Canagaratna MR; Aerodyne Research Incorporated, Billerica, MA, USA., Zaytsev A; Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA., Krechmer JE; Aerodyne Research Incorporated, Billerica, MA, USA., Breitenlechner M; Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA., Nihill KJ; Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, USA., Lim CY; Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, USA., Rowe JC; Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, USA., Roscioli JR; Aerodyne Research Incorporated, Billerica, MA, USA., Keutsch FN; Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA., Kroll JH; Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, USA.
Source: Atmospheric chemistry and physics [Atmos Chem Phys] 2020; Vol. 20 (2), pp. 1021-1041. Date of Electronic Publication: 2020 Jan 27.
Publication Type: Journal Article
Journal Info: Publisher: European Geosciences Union Country of Publication: Germany NLM ID: 101214388 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1680-7316 (Print) Linking ISSN: 16807316 NLM ISO Abbreviation: Atmos Chem Phys Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1680-7316
DOI:10.5194/acp-20-1021-2020