@COMMENT This bibtex publication entry came from Jeff Bilmes's publication pages at
@COMMENT http://melodi.ee.washington.edu/~bilmes
@COMMENT The complete bibfile can be found at:
@COMMENT http://melodi.ee.washington.edu/~bilmes/bib/bilmes.bib
@COMMENT -
@article{lin-ms1connect-2023,
    author = {Lin, Andy and Deatherage Kaiser, Brooke L and Hutchison, Janine R and Bilmes, Jeffrey A and Noble, William Stafford},
    title = "{MS1Connect: a mass spectrometry run similarity measure}",
    journal = {Bioinformatics},
    volume = {39},
    number = {2},
    year = {2023},
    month = {01},
    abstract = "{Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols.We propose a method, MS1Connect, that calculates the similarity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though these data are not used by MS1Connect.The MS1Connect software is available at https://github.com/bmx8177/MS1Connect.Supplementary data are available at Bioinformatics online.}",
    issn = {1367-4811},
    doi = {10.1093/bioinformatics/btad058},
    url = {https://doi.org/10.1093/bioinformatics/btad058},
    note = {btad058},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/39/2/btad058/49156535/btad058.pdf},
}