iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition
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DOI: 10.1371/journal.pone.0105018
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Cited by:
- Kuo Chen Chou, 2020. "How the Artificial Intelligence Tool iRNA-PseU is Working in Predicting the RNA Pseudouridine Sites?," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 24(2), pages 18055-18064, January.
- Kuo-Chen Chou, 2020. "Showcase to Illustrate How the Web-Server iKcr-PseEns is Working," International Journal of Sciences, Office ijSciences, vol. 9(01), pages 85-95, January.
- Kuo-Chen Chou, 2020. "The pLoc_bal-mGneg Predictor is a Powerful Web-Server for Identifying the Subcellular Localization of Gram-Negative Bacterial Proteins based on their Sequences Information Alone," International Journal of Sciences, Office ijSciences, vol. 9(01), pages 27-34, January.
- Abdollah Dehzangi & Yosvany López & Sunil Pranit Lal & Ghazaleh Taherzadeh & Abdul Sattar & Tatsuhiko Tsunoda & Alok Sharma, 2018. "Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-16, February.
- Sabit Ahmed & Afrida Rahman & Md Al Mehedi Hasan & Md Khaled Ben Islam & Julia Rahman & Shamim Ahmad, 2021. "predPhogly-Site: Predicting phosphoglycerylation sites by incorporating probabilistic sequence-coupling information into PseAAC and addressing data imbalance," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-17, April.
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