亚细胞定位是指某种蛋白或某个基因表达产物在细胞内的具体存在部位，包括细胞核、细胞质和细胞膜以及各种细胞器等。
下面是一篇文章对各种工具做了汇总和比较：
| Tool Name | Locations or Protein Features Predicted | Organism Categories | Publication Reference |
|---|---|---|---|
| TargetP | extracellular, mitochondrial, chloroplast | non-plant, plant | Emanuelsson, O., Nielsen, H., Brunak, S., & von Heijne, G. (2000) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. Journal of molecular biology, 300(4), 1005-1016. |
| TMHMM | transmembrane helices | any | Krogh, A., Larsson, B., von Heijne, G., & Sonnhammer, E. L. (2001) Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. Journal of molecular biology, 305(3), 567-580. |
| scanProsite (PS-Scan) | ER retention signal | any | de Castro E, Sigrist CJ, Gattiker A, Bulliard V, Langendijk-Genevaux PS, Gasteiger E, Bairoch A, Hulo N. (2006) ScanProsite: detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins. Nucleic Acids Res., 34(Web Server issue), W362-365. |
| SecretomeP 2.0 | non-classical i.e. not signal peptide triggered protein secretion | gram-positive bacteria, gram-negative bacteria, mammal | Bendtsen J.D., Jensen,L.J., Blom,N., et al. (2004) Feature based prediction of non-classical and leaderless protein secretion. Protein Eng. Des. Sel., 17, 349-356. |
| Phobius | signal peptide and transmembrane topology | any | Käll, L., Krogh, A., & Sonnhammer, E. L. L. (2007) Advantages of combined transmembrane topology and signal peptide prediction–the Phobius web server.. Nucleic Acids Res., 35(Web Server issue), W429-432. |
| WoLF PSORT | > 5 locations | fungi, plant, animal | Horton, P., Park, K.-J., Obayashi, T., Fujita, N., Harada, H., Adams-Collier, C. J., & Nakai, K. (2007) WoLF PSORT: protein localization predictor. Nucleic Acids Res., 35(Web Server issue), W585-587. |
| PRED-LIPO | lipoprotein signal peptides | gram-positive bacteria | Bagos, Pantelis G, Tsirigos, K. D., Liakopoulos, T. D., & Hamodrakas, S. J. (2008) Prediction of lipoprotein signal peptides in Gram-positive bacteria with a Hidden Markov Model. Journal of proteome research, 7(12), 5082-5093. |
| ProLoc-GO | > 5 locations | human and eukaryotes | Huang, W.-L., Tung, C.-W., Ho, S.-W., Hwang, S.-F., & Ho, S.-Y. (2008) ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. BMC bioinformatics, 9, 80. |
| KnowPredsite | > 5 locations | prokaryotes and eukaryotes | Lin, H.-N., Chen, C.-T., Sung, T.-Y., Ho, S.-Y., & Hsu, W.-L. (2009) Protein subcellular localization prediction of eukaryotes using a knowledge-based approach. BMC bioinformatics, 10 Suppl 15, S8. |
| MultiLoc2 | > 5 locations | animal, fungal, plant | Blum, T, Briesemeister, S, and Kohlbacher, O (2009) MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction. BMC Bioinformatics, 10:274. |
| PRED-SIGNAL | signal peptides | archaea | Bagos, P G, Tsirigos, K. D., Plessas, S. K., Liakopoulos, T. D., & Hamodrakas, S. J. (2009) Prediction of signal peptides in archaea. Protein engineering, design & selection: PEDS, 22(1), 27-35. |
| RSLPred | chloroplast, cytoplasm, mitochondria, nucleus | oryza sativa only | Kaundal, R., & Raghava, G. P. S. (2009) RSLpred: an integrative system for predicting subcellular localization of rice proteins combining compositional and evolutionary information. Proteomics, 9(9), 2324-2342. |
| SherLoc2 | > 5 locations | animal, fungi, plant | Briesemeister, S., Blum, T., Brady, S., Lam, Y., Kohlbacher, O., & Shatkay, H. (2009) SherLoc2: a high-accuracy hybrid method for predicting subcellular localization of proteins. Journal of proteome research, 8(11), 5363-5366. |
| Cell-PLoc 2.0 | > 5 locations | eukaryote, human, plant, virus, gram-positive bacteria, gram-negative bacteria | Chou, K. and Shen, H. (2010) Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms. Natural Science, 2, 1090-1103. |
| CoBaltDB | > 5 locations | prokaryotes | Goudenège, D., Avner, S., Lucchetti-Miganeh, C., & Barloy-Hubler, F. (2010) CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources. BMC microbiology, 10, 88. |
| PSORTb | > 5 locations | gram-positive and gram-negative bacteria | Yu, N. Y., Wagner, J. R., Laird, M. R., Melli, G., Rey, S., Lo, R., … Brinkman, F. S. L. (2010) PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics (Oxford, England), 26(13), 1608-1615. |
| SCLPred | cytoplasm, mitochondrion, nucleus, secretory, chloroplast | animals, plants, fungi | Mooney, C., Wang, Y.-H., & Pollastri, G. (2011) SCLpred: protein subcellular localization prediction by N-to-1 neural networks. Bioinformatics (Oxford, England), 27(20), 2812-2819. |
| SignalP 4.0 | signal peptide | eukaryotic, gram-positive bacteria, gram-negative bacteria | Petersen, T. N., Brunak, S., von Heijne, G., & Nielsen, H. (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nature methods, 8(10), 785-786. |
| SlocX | > 5 locations | aribdopsis thaliana only | Ryngajllo, M., Childs, L., Lohse, M., Giorgi, F. M., Lude, A., Selbig, J., & Usadel, B. (2011) SLocX: Predicting Subcellular Localization of Arabidopsis Proteins Leveraging Gene Expression Data. Frontiers in plant science, 2, 43. |
| APSLAP | > 5 locations | apoptosis | Saravanan, V., & Lakshmi, P. T. V. (2013) APSLAP: An Adaptive Boosting Technique for Predicting Subcellular Localization of Apoptosis Protein. Acta biotheoretica, . |
| Iloc Animal | > 5 locations | animal | Lin, W.-Z., Fang, J.-A., Xiao, X., & Chou, K.-C. (2013) iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins. Molecular bioSystems, 9(4), 634-644. |
参考资料：
1. Meinken J, Min XJ. (2012) Computational prediction of protein subcellular locations in eukaryotes: an experience report. Computational Molecular Biology. 2(1): 1-7 (doi: 10.5376/cmb.2012.02.0001).
