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