The DOI matches its Crossref record; 105 of the 105 references it cites were found in a registry or an index.
Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms
Open accessAbstract
Cell-PLoc 2.0 is a package of web-servers evolved from Cell-PLoc (Chou, K.C. & Shen, H.B., Nature Protocols, 2008, 2:153-162) by a top-down approach to improve the power for predicting subcellular localization of proteins in various organisms. It contains six predictors: Euk-mPLoc 2.0, Hum-mPLoc 2.0, Plant-mPLoc, Gpos-mPLoc, Gneg-mPLoc, and Virus-mPLoc, specialized for eukaryotic, human, plant, Gram- positive bacterial, Gram-negative bacterial, and virus proteins, respectively. Compared with Cell-PLoc, the predictors in the Cell-PLoc 2.0 have the following advantageous features: (1) they all have the capacity to deal with the multiplex proteins that can simultaneiously exist, or move between, two or more subcellular location sites; (2) no accession number is needed for the input of a query protein even if using the “high- level” GO (gene ontology) prediction engine; (3) the functional domain information and sequential evolution information are fused into the “ab initio” sequence-based prediction engine to enhance its accuracy. In this protocol, a step- to-step guide is provided for how to use the web server predictors in the Cell-PLoc 2.0 package, which is freely accessible to the public at http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/.
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Cites
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Self-citationChou, K.-C., & Shen, H.-B. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011335 · Cited by 1,157
Self-citationPrediction of Protein Structural Classes
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Self-citationUsing amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
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Self-citationSupport vector machine approach for protein subcellular localization prediction
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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-citationIdentification of Antioxidants from Sequence Information Using Naïve Bayes
Feng, P.-M., Lin, H., & Chen, W. (2013) · Computational and Mathematical Methods in Medicine · doi:10.1155/2013/567529 · Cited by 109
Wei, Z., Liu, X., Yan, R., Sun, G., Yu, W., Liu, Q., & Guo, Q. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.1002327 · Cited by 7
Metadata
- Authors
- Chou, K.-C., & Shen, H.-B.
- Venue
- Natural Science
- Publisher
- Scientific Research Publishing, Inc.
- Published
- 2010
- Volume
- 02
- Issue
- 10
- Pages
- 1090-1103
- ISSN
- 2150-4091 (ISSN-L)
- 2150-4105
- OpenAlex
- W1970399546
- Cited by
- 347
- References
- 105
- FWCI
- 11.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
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