The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties
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Citations
Cites
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Proceedings of the National Academy of Sciences of the United States of America
Dowling, J. E., & Wald, G. (2009) · Nutrition Reviews · doi:10.1111/j.1753-4887.1981.tb06752.x · Cited by 17,893
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Cristianini, N., & Shawe-Taylor, J. (2000) · doi:10.1017/cbo9780511801389 · Cited by 13,855
The relationship between Precision-Recall and ROC curves
Davis, J., & Goadrich, M. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143874 · Cited by 6,559
Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq
Dominissini, D., Moshitch-Moshkovitz, S., Schwartz, S., Salmon-Divon, M., Ungar, L., Osenberg, S., Cesarkas, K., Jacob-Hirsch, J., Amariglio, N., Kupiec, M., et al. (2012) · Nature · doi:10.1038/nature11112 · Cited by 4,884
N6-Methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO
Jia, G., Fu, Y., Zhao, X., Dai, Q., Zheng, G., Yang, Y., Yi, C., Lindahl, T., Pan, T., Yang, Y.-G., et al. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.687 · Cited by 4,106
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Prediction of protein cellular attributes using pseudo‐amino acid composition
Chou, K. (2001) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.1035 · Cited by 1,943
Self-citationWhat's In A Name? Malay Seals As Onomastic Sources
Library, T. B., & Gallop, A. T. (2018) · Malay Literature · doi:10.37052/ml.31(1)no1 · Cited by 1,483
Improved free-energy parameters for predictions of RNA duplex stability.
Freier, S. M., Kierzek, R., Jaeger, J. A., Sugimoto, N., Caruthers, M. H., Neilson, T., & Turner, D. H. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.24.9373 · Cited by 1,470
Cited by
Liu, B., Yang, F., Huang, D.-S., & Chou, K.-C. (2018) · Bioinformatics · doi:10.1093/bioinformatics/btx579 · Cited by 331
Self-citationiRNA-PseU: Identifying RNA pseudouridine sites
Chen, W., Tang, H., Ye, J., Lin, H., & Chou, K.-C. (2016) · Molecular Therapy - Nucleic Acids · doi:10.1038/mtna.2016.37 · Cited by 291
Self-citationWei, L., Chen, H., & Su, R. (2018) · Molecular Therapy Nucleic Acids · doi:10.1016/j.omtn.2018.07.004 · Cited by 179
Metadata
- Authors
- Liu, Z., Xiao, X., Yu, D.-J., Jia, J., Qiu, W.-R., & Chou, K.-C.
- Venue
- Analytical Biochemistry
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 497
- Pages
- 60-67
- ISSN
- 0003-2697 (ISSN-L)
- OpenAlex
- W2205505631
- Cited by
- 257
- References
- 86
- FWCI
- 16.34
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties. https://app.cochat.ai/papers/10.1016/j.ab.2015.12.017
- The paper
- Liu, Z., Xiao, X., Yu, D.-J., Jia, J., Qiu, W.-R., & Chou, K.-C. (2016). pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties. Analytical Biochemistry. https://doi.org/10.1016/j.ab.2015.12.017
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.
