Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

Gray Huffman, View ORCID ProfileHarrison Specht, View ORCID ProfileAlbert Chen, View ORCID ProfileNikolai Slavov
doi: https://doi.org/10.1101/512152
Gray Huffman
†Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Harrison Specht
†Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Harrison Specht
Albert Chen
†Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Albert Chen
Nikolai Slavov
†Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
‡Department of Biology, Northeastern University, Boston, MA 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Nikolai Slavov
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/512152
History 
  • January 6, 2019.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Author Information

  1. Gray Huffman†,
  2. Harrison Specht†,
  3. Albert Chen† and
  4. Nikolai Slavov*,†,‡
  1. †Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
  2. Barnett Institute, Northeastern University, Boston, MA 02115, USA
  3. ‡Department of Biology, Northeastern University, Boston, MA 02115, USA
Back to top
PreviousNext
Posted January 06, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
DO-MS: Data-Driven Optimization of Mass Spectrometry Methods
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
DO-MS: Data-Driven Optimization of Mass Spectrometry Methods
Gray Huffman, Harrison Specht, Albert Chen, Nikolai Slavov
bioRxiv 512152; doi: https://doi.org/10.1101/512152
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
DO-MS: Data-Driven Optimization of Mass Spectrometry Methods
Gray Huffman, Harrison Specht, Albert Chen, Nikolai Slavov
bioRxiv 512152; doi: https://doi.org/10.1101/512152

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4655)
  • Biochemistry (10307)
  • Bioengineering (7618)
  • Bioinformatics (26203)
  • Biophysics (13453)
  • Cancer Biology (10625)
  • Cell Biology (15348)
  • Clinical Trials (138)
  • Developmental Biology (8456)
  • Ecology (12761)
  • Epidemiology (2067)
  • Evolutionary Biology (16777)
  • Genetics (11361)
  • Genomics (15407)
  • Immunology (10556)
  • Microbiology (25060)
  • Molecular Biology (10162)
  • Neuroscience (54128)
  • Paleontology (398)
  • Pathology (1655)
  • Pharmacology and Toxicology (2877)
  • Physiology (4315)
  • Plant Biology (9204)
  • Scientific Communication and Education (1582)
  • Synthetic Biology (2543)
  • Systems Biology (6753)
  • Zoology (1453)