The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties
Abstract
Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties play key roles in the discovery/development of drugs, pesticides, food additives, consumer products, and industrial chemicals. This information is especially useful when to conduct environmental and human hazard assessment. The most critical rate limiting step in the chemical safety assessment workflow is the availability of high quality data. This paper describes an ADMET structure-activity relationship database, abbreviated as admetSAR. It is an open source, text and structure searchable, and continually updated database that collects, curates, and manages available ADMET-associated properties data from the published literature. In admetSAR, over 210,000 ADMET annotated data points for more than 96,000 unique compounds with 45 kinds of ADMET-associated properties, proteins, species, or organisms have been carefully curated from a large number of diverse literatures. The database provides a user-friendly interface to query a specific chemical profile, using either CAS registry number, common name, or structure similarity. In addition, the database includes 22 qualitative classification and 5 quantitative regression models with highly predictive accuracy, allowing to estimate ecological/mammalian ADMET properties for novel chemicals. AdmetSAR is accessible free of charge at http://www.admetexp.org.
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
Can the pharmaceutical industry reduce attrition rates?
Kola, I., & Landis, J. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1470 · Cited by 4,167
Quantitative Structure−Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure
Zhu, H., Martin, T. M., Ye, L., Sedykh, A., Young, D. M., & Tropsha, A. (2009) · Chemical Research in Toxicology · doi:10.1021/tx900189p · Cited by 287
Fourches, D., Barnes, J. C., Day, N. C., Bradley, P., Reed, J. Z., & Tropsha, A. (2010) · Chemical Research in Toxicology · doi:10.1021/tx900326k · Cited by 162
Cited by
Daina, A., Michielin, O., & Zoete, V. (2017) · Scientific Reports · doi:10.1038/srep42717 · Cited by 18,367
The neuroactive potential of the human gut microbiota in quality of life and depression
Valles-Colomer, M., Falony, G., Darzi, Y., Tigchelaar, E. F., Wang, J., Tito, R. Y., Schiweck, C., Kurilshikov, A., Joossens, M., Wijmenga, C., et al. (2019) · Nature Microbiology · doi:10.1038/s41564-018-0337-x · Cited by 1,963
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021) · Molecular Diversity · doi:10.1007/s11030-021-10217-3 · Cited by 1,473
“For this different web-based tools have been developed such as LimTox (http:// limtox. bioin fo. cnio. es/) [321], pkCSM (http:// biosig. unime lb. edu. au/ pkcsm/) [322], admetSAR (http:// lmmd. ecust. edu. cn/ admet sar2/) [323], and Toxtree (http:// toxtr ee. sourc eforge. net/) [324].”
MethodBlockchain and Artificial Intelligence Technology in E-Health
Tagde, P., Tagde, S., Bhattacharya, T., Tagde, P., Chopra, H., Akter, R., Kaushik, D., & Rahman, M. H. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-16223-0 · Cited by 281
Temozolomide and Other Alkylating Agents in Glioblastoma Therapy
Strobel, H., Baisch, T., Fitzel, R., Schilberg, K., Siegelin, M. D., Karpel-Massler, G., Debatin, K.-M., & Westhoff, M.-A. (2019) · Biomedicines · doi:10.3390/biomedicines7030069 · Cited by 279
Metadata
- Authors
- Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., Lee, P. W., & Tang, Y.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-11-01
- Volume
- 52
- Issue
- 11
- Pages
- 3099-3105
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2014858249
- Cited by
- 2,222
- References
- 3
- FWCI
- 30.54
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. https://app.cochat.ai/papers/10.1021/ci300367a
- The paper
- Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., Lee, P. W., & Tang, Y. (2012). admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. Journal of Chemical Information and Modeling. https://doi.org/10.1021/ci300367a
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.