The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types
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
CRC Handbook of Chemistry and Physics
(2014) · doi:10.1201/b17118 · Cited by 57,706
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
Kohavi, R. (1995) · Zenodo · doi:10.5281/zenodo.19712698 · Cited by 10,909
Some remarks on protein attribute prediction and pseudo amino acid composition
Chou, K.-C. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.12.024 · Cited by 1,225
Self-citation
Cited by
APD3: the antimicrobial peptide database as a tool for research and education
Wang, G., Li, X., & Wang, Z. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1278 · Cited by 2,388
Deep learning improves antimicrobial peptide recognition
Veltri, D., Kamath, U., & Shehu, A. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty179 · Cited by 593
Lin, H., Deng, E.-Z., Ding, H., Chen, W., & Chou, K.-C. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1019 · Cited by 508
Self-citationIdentification of antimicrobial peptides from the human gut microbiome using deep learning
Ma, Y., Guo, Z., Xia, B., Zhang, Y., Liu, X., Yu, Y., Tang, N., Tong, X., Wang, M., Ye, X., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01226-0 · Cited by 490
Guo, S.-H., Deng, E.-Z., Xu, L.-Q., Ding, H., Lin, H., Chen, W., & Chou, K.-C. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu083 · Cited by 375
Self-citation
Metadata
- Authors
- Xiao, X., Wang, P., Lin, W.-Z., Jia, J.-H., & Chou, K.-C.
- Venue
- Analytical Biochemistry
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 436
- Issue
- 2
- Pages
- 168-177
- ISSN
- 0003-2697 (ISSN-L)
- OpenAlex
- W1998064689
- Cited by
- 547
- References
- 3
- FWCI
- 40.92
- 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: iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types. https://app.cochat.ai/papers/10.1016/j.ab.2013.01.019
- The paper
- Xiao, X., Wang, P., Lin, W.-Z., Jia, J.-H., & Chou, K.-C. (2013). iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types. Analytical Biochemistry. https://doi.org/10.1016/j.ab.2013.01.019
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.