The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Molecular Similarity Searching Using Atom Environments, Information-Based Feature Selection, and a Naïve Bayesian Classifier
Abstract
A novel technique for similarity searching is introduced. Molecules are represented by atom environments, which are fed into an information-gain-based feature selection. A naïve Bayesian classifier is then employed for compound classification. The new method is tested by its ability to retrieve five sets of active molecules seeded in the MDL Drug Data Report (MDDR). In comparison experiments, the algorithm outperforms all current retrieval methods assessed here using two- and three-dimensional descriptors and offers insight into the significance of structural components for binding.
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
Cites
Cramer, R. D., Patterson, D. E., & Bunce, J. D. (1988) · Journal of the American Chemical Society · doi:10.1021/ja00226a005 · Cited by 3,931
Cited by
DeepTox: toxicity prediction using deep learning
Mayr, A., Klambauer, G., Unterthiner, T., & Hochreiter, S. (2016) · Frontiers in Environmental Science · doi:10.3389/fenvs.2015.00080 · Cited by 1,081
Sastry, M., Lowrie, J. F., Dixon, S. L., & Sherman, W. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci100062n · Cited by 332
Matched Molecular Pairs as a Medicinal Chemistry Tool: Miniperspective
Griffen, E., Leach, A. G., Robb, G. R., & Warner, D. J. (2011) · Journal of Medicinal Chemistry · doi:10.1021/jm200452d · Cited by 282
Ursu, O., Rayan, A., Goldblum, A., & Oprea, T. I. (2011) · WIREs Computational Molecular Science · doi:10.1002/wcms.52 · Cited by 276
Peltason, L., Iyer, P., & Bajorath, J. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci100091e · Cited by 85
Metadata
- Authors
- Bender, A., Mussa, H. Y., Glen, R. C., & Reiling, S.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-12-24
- Volume
- 44
- Issue
- 1
- Pages
- 170-178
- ISSN
- 0095-2338 (ISSN-L)
- OpenAlex
- W1983610905
- Cited by
- 246
- References
- 1
- FWCI
- 8.74
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.
