Artificial intelligence in mass spectrometry-based proteomics

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Standard

Artificial intelligence in mass spectrometry-based proteomics. / Zeng, Wen Feng; Mann, Matthias; Strauss, Maximillian T.

Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics. Elsevier, 2024. p. 389-394.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Zeng, WF, Mann, M & Strauss, MT 2024, Artificial intelligence in mass spectrometry-based proteomics. in Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics. Elsevier, pp. 389-394. https://doi.org/10.1016/B978-0-443-15688-5.00010-3

APA

Zeng, W. F., Mann, M., & Strauss, M. T. (2024). Artificial intelligence in mass spectrometry-based proteomics. In Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics (pp. 389-394). Elsevier. https://doi.org/10.1016/B978-0-443-15688-5.00010-3

Vancouver

Zeng WF, Mann M, Strauss MT. Artificial intelligence in mass spectrometry-based proteomics. In Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics. Elsevier. 2024. p. 389-394 https://doi.org/10.1016/B978-0-443-15688-5.00010-3

Author

Zeng, Wen Feng ; Mann, Matthias ; Strauss, Maximillian T. / Artificial intelligence in mass spectrometry-based proteomics. Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics. Elsevier, 2024. pp. 389-394

Bibtex

@inbook{18ff25fea4044e648f7a6e98929ad13b,
title = "Artificial intelligence in mass spectrometry-based proteomics",
abstract = "Advances in mass spectrometry-based proteomics enable researchers to acquire large-scale datasets with hundreds to thousands of samples. Artificial intelligence (AI) technologies are now applied across the entire proteomics workflow and can be used to distill meaningful insight from clinical proteomics data. While there are still substantial challenges, proteomics-fueled AI has great potential to improve health outcomes.",
keywords = "artificial intelligence, deep learning, Machine learning, mass spectrometry, proteome, proteomics",
author = "Zeng, {Wen Feng} and Matthias Mann and Strauss, {Maximillian T.}",
note = "Publisher Copyright: {\textcopyright} 2024 Elsevier Inc. All rights reserved.",
year = "2024",
doi = "10.1016/B978-0-443-15688-5.00010-3",
language = "English",
isbn = "9780443156892",
pages = "389--394",
booktitle = "Artificial Intelligence in Clinical Practice",
publisher = "Elsevier",
address = "Netherlands",

}

RIS

TY - CHAP

T1 - Artificial intelligence in mass spectrometry-based proteomics

AU - Zeng, Wen Feng

AU - Mann, Matthias

AU - Strauss, Maximillian T.

N1 - Publisher Copyright: © 2024 Elsevier Inc. All rights reserved.

PY - 2024

Y1 - 2024

N2 - Advances in mass spectrometry-based proteomics enable researchers to acquire large-scale datasets with hundreds to thousands of samples. Artificial intelligence (AI) technologies are now applied across the entire proteomics workflow and can be used to distill meaningful insight from clinical proteomics data. While there are still substantial challenges, proteomics-fueled AI has great potential to improve health outcomes.

AB - Advances in mass spectrometry-based proteomics enable researchers to acquire large-scale datasets with hundreds to thousands of samples. Artificial intelligence (AI) technologies are now applied across the entire proteomics workflow and can be used to distill meaningful insight from clinical proteomics data. While there are still substantial challenges, proteomics-fueled AI has great potential to improve health outcomes.

KW - artificial intelligence

KW - deep learning

KW - Machine learning

KW - mass spectrometry

KW - proteome

KW - proteomics

U2 - 10.1016/B978-0-443-15688-5.00010-3

DO - 10.1016/B978-0-443-15688-5.00010-3

M3 - Book chapter

AN - SCOPUS:85176843312

SN - 9780443156892

SP - 389

EP - 394

BT - Artificial Intelligence in Clinical Practice

PB - Elsevier

ER -

ID: 375308340