The DOI matches its Crossref record.
Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider
Open accessAbstract
In many cases, an unknown to an investigator is actually known in the chemical literature, a reference database, or an internet resource. We refer to these types of compounds as "known unknowns." ChemSpider is a very valuable internet database of known compounds useful in the identification of these types of compounds in commercial, environmental, forensic, and natural product samples. The database contains over 26 million entries from hundreds of data sources and is provided as a free resource to the community. Accurate mass mass spectrometry data is used to query the database by either elemental composition or a monoisotopic mass. Searching by elemental composition is the preferred approach. However, it is often difficult to determine a unique elemental composition for compounds with molecular weights greater than 600 Da. In these cases, searching by the monoisotopic mass is advantageous. In either case, the search results are refined by sorting the number of references associated with each compound in descending order. This raises the most useful candidates to the top of the list for further evaluation. These approaches were shown to be successful in identifying "known unknowns" noted in our laboratory and for compounds of interest to others.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Wang, M., Carver, J. J., Phelan, V. V., Sanchez, L. M., Garg, N., Peng, Y., Nguyen, D. D., Watrous, J., Kapono, C. A., Luzzatto-Knaan, T., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3597 · Cited by 4,629
MetFrag relaunched: incorporating strategies beyond in silico fragmentation
Ruttkies, C., Schymanski, E. L., Wolf, S., Hollender, J., & Neumann, S. (2016) · Journal of Cheminformatics · doi:10.1186/s13321-016-0115-9 · Cited by 1,052
High-confidence structural annotation of metabolites absent from spectral libraries
Hoffmann, M. A., Nothias, L.-F., Ludwig, M., Fleischauer, M., Gentry, E. C., Witting, M., Dorrestein, P. C., Dührkop, K., & Böcker, S. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01045-9 · Cited by 388
Metadata
- Authors
- Little, J. L., Williams, A. J., Pshenichnov, A., & Tkachenko, V.
- Venue
- Journal of the American Society for Mass Spectrometry
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-11-02
- Volume
- 23
- Issue
- 1
- Pages
- 179-185
- ISSN
- 1044-0305 (ISSN-L)
- OpenAlex
- W1986517195
- Cited by
- 168
- References
- 0
- FWCI
- 4.79
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider. https://app.cochat.ai/papers/10.1007/s13361-011-0265-y
- The paper
- Little, J. L., Williams, A. J., Pshenichnov, A., & Tkachenko, V. (2012). Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider. Journal of the American Society for Mass Spectrometry. https://doi.org/10.1007/s13361-011-0265-y
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.