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PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization
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“Using PSORT II, a program for predicting protein subcellular localization sites22, no putative NLS was identified in CRBN; however, CRBN was predicated to be nuclear using both PSORT II and PredictNLS.”
From Genome-wide screening reveals a role for subcellular localization of CRBN in the anti-myeloma activity of pomalidomide (2020) · cites this paper as [22]
In the citing paper
“Using PSORT II, a program for predicting protein subcellular localization sites22, no putative NLS was identified in CRBN; however, CRBN was predicated to be nuclear using both PSORT II and PredictNLS.”
From Genome-wide screening reveals a role for subcellular localization of CRBN in the anti-myeloma activity of pomalidomide (2020) · cites this paper as [22]
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Sorted by citations
Improved Prediction of Signal Peptides: SignalP 3.0
Dyrløv Bendtsen, J., Nielsen, H., von Heijne, G., & Brunak, S. (2004) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.05.028 · Cited by 6,350
The hormone resistin links obesity to diabetes
Steppan, C. M., Bailey, S. T., Bhat, S., Brown, E. J., Banerjee, R. R., Wright, C. M., Patel, H. R., Ahima, R. S., & Lazar, M. A. (2001) · Nature · doi:10.1038/35053000 · Cited by 4,755
“A notable feature of the deduced amino-acid sequence of resistin is a hydrophobic amino terminus that is predicted by the Prosor”
BackgroundWoLF PSORT: protein localization predictor
Horton, P., Park, K., Obayashi, T., Fujita, N., Harada, H., Adams-Collier, C. J., & Nakai, K. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm259 · Cited by 4,154
“WoLF PSORT is an extension of PSORT II (13, 14 ) and also uses the PSORT (15) localization features for prediction.”
Self-citationSequence and structure-based prediction of eukaryotic protein phosphorylation sites
Blom, N., Gammeltoft, S., & Brunak, S. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3310 · Cited by 3,212
Complete genome sequence of Salmonella enterica serovar Typhimurium LT2
McClelland, M., Sanderson, K. E., Spieth, J., Clifton, S. W., Latreille, P., Courtney, L., Porwollik, S., Ali, J., Dante, M., Du, F., et al. (2001) · Nature · doi:10.1038/35101614 · Cited by 1,838
Translocation of Proteins into Mitochondria
Neupert, W., & Herrmann, J. M. (2007) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.76.052705.163409 · Cited by 1,486
Zhang, H., Li, X., Martin, D. B., & Aebersold, R. H. (2003) · Nature Biotechnology · doi:10.1038/nbt827 · Cited by 1,390
RNA Interference: Biology, Mechanism, and Applications
Agrawal, N., Dasaradhi, P. V. N., Mohmmed, A., Malhotra, P., Bhatnagar, R. K., & Mukherjee, S. K. (2003) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.67.4.657-685.2003 · Cited by 1,373
“MUT6 also has three putative nuclear localization signals and is predicted to be nuclear by PSORT analysis (161).”
BackgroundThe rde-1 Gene, RNA Interference, and Transposon Silencing in C. elegans
Tabara, H., Sarkissian, M., Kelly, W. G., Fleenor, J., Grishok, A., Timmons, L., Fire, A. Z., & Mello, C. C. (1999) · Cell · doi:10.1016/s0092-8674(00)81644-x · Cited by 1,307
“be cytoplasmic or nuclear by PSORT analysis (Nakai and Horton, 1999).”
BackgroundMethodKosugi, S., Hasebe, M., Tomita, M., & Yanagawa, H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900604106 · Cited by 1,278
“The program’s prediction performance was compared with those of 2 other available methods, PSORT II (21) and PredictNLS (22), which are based on the traditional consensus sequence of the classical NLS and in silico mutagenesis analysis with several NLSs collected from the literature, respectively (Table 1).”
MethodChou, K., & Shen, H. (2008) · Nature Protocols · doi:10.1038/nprot.2007.494 · Cited by 1,226
Feature-based prediction of non-classical and leaderless protein secretion
Bendtsen, J. D., Jensen, L. J., Blom, N., von HEIJNE, G., & Brunak, S. (2004) · Protein Engineering Design and Selection · doi:10.1093/protein/gzh037 · Cited by 1,179
“PSORT does not predict secreted proteins lacking their signal peptide to be secreted, but predicts them to be cytoplasmic or nuclear.”
BackgroundMethodInfluentialClassical Nuclear Localization Signals: Definition, Function, and Interaction with Importin α
Lange, A., Mills, R. E., Lange, C. J., Stewart, M., Devine, S. E., & Corbett, A. H. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.r600026200 · Cited by 1,168
Mitochondrial Import Efficiency of ATFS-1 Regulates Mitochondrial UPR Activation
Nargund, A. M., Pellegrino, M., Fiorese, C. J., Baker, B. M., & Haynes, C. M. (2012) · Science · doi:10.1126/science.1223560 · Cited by 1,027
Control of mitochondrial morphology by a human mitofusin
Santel, A., & Fuller, M. T. (2001) · Journal of Cell Science · doi:10.1242/jcs.114.5.867 · Cited by 1,012
Mootha, V. K., Bunkenborg, J., Olsen, J. V., Hjerrild, M., Wisniewski, J. R., Stahl, E., Bolouri, M. S., Ray, H. N., Sihag, S., Kamal, M., et al. (2003) · Cell · doi:10.1016/s0092-8674(03)00926-7 · Cited by 889
“…with genome-wide expression microarfind evidence by bioinformatic analysis (Claros, 1995; rays, it should be possible to more comprehensively Nakai and Horton, 1999) that these two proteins contain reconstruct pathways within the mitochondrion and to reasonable mitochondrial targeting…”
BackgroundCollection, Mapping, and Annotation of Over 28,000 cDNA Clones from japonica Rice
Kikuchi, S., Satoh, K., Nagata, T., Kawagashira, N., Doi, K., Kishimoto, N., Yazaki, J., Ishikawa, M., Yamada, H., Ooka, H., et al. (2003) · Science · doi:10.1126/science.1081288 · Cited by 869
Recent progress in protein subcellular location prediction
Chou, K., & Shen, H. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.07.006 · Cited by 769
“During the past 15 years, a variety of predictors have been developed to deal with the challenge [7–39].”
BackgroundPre- and Postinvasion Defenses Both Contribute to Nonhost Resistance in Arabidopsis
Lipka, V., Dittgen, J., Bednarek, P., Bhat, R., Wiermer, M., Stein, M., Landtag, J., Brandt, W., Rosahl, S., Scheel, D., et al. (2005) · Science · doi:10.1126/science.1119409 · Cited by 768
Genes involved in matrix formation in Pseudomonas aeruginosa PA14 biofilms
Friedman, L., & Kolter, R. (2003) · Molecular Microbiology · doi:10.1046/j.1365-2958.2003.03877.x · Cited by 728
“PSORT was used tentatively to predict the cellular location and transmembrane domains of the predicted proteins (Nakai and Horton, 1999).”
MethodComplete genome sequence of Clostridium perfringens , an anaerobic flesh-eater
Shimizu, T., Ohtani, K., Hirakawa, H., Ohshima, K., Yamashita, A., Shiba, T., Ogasawara, N., Hattori, M., Kuhara, S., & Hayashi, H. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.022493799 · Cited by 726
Extensive feature detection of N-terminal protein sorting signals
Bannai, H., Tamada, Y., Maruyama, O., Nakai, K., & Miyano, S. (2002) · Bioinform. · doi:10.1093/bioinformatics/18.2.298 · Cited by 746
“PSORT (Nakai and Kanehisa, 1992; Nakai and Horton, 1999) and MitoProt (Claros and Vincens, 1996), unlike TargetP, are systems which incorporate existing knowledge about sorting signals, but they use various real numbers as " weights " in their prediction rules which also may not be trivially…”
BackgroundSelf-citationNon-classical protein secretion in bacteria
Bendtsen, J. D., Kiemer, L., Fausbøll, A., & Brunak, S. (2005) · BMC Microbiology · doi:10.1186/1471-2180-5-58 · Cited by 709
“PSORTb version 2 [49] classified correctly as 'extracellular' five of the proteins with known extracellular function, while the remaining were classified either as 'cytoplasmic' or 'unknown'.”
MethodResultInfluentialNLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction
Ba, A. N. N., Pogoutse, A. K., Provart, N. J., & Moses, A. M. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-202 · Cited by 697
“PSORT [7] accurately predicts protein localization by including heuristic scores based on residues frequencies, protein domains as well as motifs.”
MethodGenome Structure of the Legume, Lotus japonicus
Sato, S., Nakamura, Y., Kaneko, T., Asamizu, E., Kato, T., Nakao, M., Sasamoto, S., Watanabe, A., Ono, A., Kawashima, K., et al. (2008) · DNA Research · doi:10.1093/dnares/dsn008 · Cited by 700
Modeling aspects of the language of life through transfer-learning protein sequences
Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3220-8 · Cited by 606
Plasticity in the organization and sequences of human KIR/ILT gene families
Wilson, M. J., Torkar, M., Haude, A., Milne, S., Jones, T. A., Sheer, D., Beck, S., & Trowsdale, J. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.080588597 · Cited by 624
Modeling the language of life – Deep Learning Protein Sequences
Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · doi:10.1101/614313 · Cited by 606
“This concept resembles 24 that of using k-mers for database searches [33], clustering [74], motifs [75, 76], and prediction 25 methods [66, 70, 77-81].”
MethodThe Mitochondrial Proteome and Human Disease
Calvo, S. E., & Mootha, V. K. (2010) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-082509-141720 · Cited by 590
“These include TargetP (31), pTARGET (41), PSORT (77), iPSORT (9), Predotar (97), ngLoc (52), MitPred (59), MitoPred (42), and MitoProt (21), as described in a recent comparative review (40).”
Disarming the mustard oil bomb
Ratzka, A., Vogel, H., Kliebenstein, D. J., Mitchell‐Olds, T., & Kroymann, J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.172112899 · Cited by 595
Current challenges and best-practice protocols for microbiome analysis
Bharti, R., & Grimm, D. G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbz155 · Cited by 592
NLRX1 is a regulator of mitochondrial antiviral immunity
Moore, C. B., Bergstralh, D. T., Duncan, J. A., Lei, Y. L., Morrison, T. E., Zimmermann, A. G., Accavitti-Loper, M. A., Madden, V. J., Sun, L., Ye, Z., et al. (2008) · Nature · doi:10.1038/nature06501 · Cited by 599
Heazlewood, J. L., Tonti‐Filippini, J., Gout, A. M., Day, D. A., Whelan, J., & Millar, A. H. (2004) · The Plant Cell · doi:10.1105/tpc.016055 · Cited by 575
“MitoProt II (Claros and Vincens, 1996), PSORT (Nakai and Horton, 1999), and iPSORT (Bannai et al., 2002) use predefined parameters of signal peptides to predict subcellular localization.”
MethodRongvaux, A., Shea, R. J., Mulks, M. H., Gigot, D., Urbain, J., Léo, O., & Andris, F. (2002) · European Journal of Immunology · doi:10.1002/1521-4141(200211)32:11 · Cited by 551
APPL Proteins Link Rab5 to Nuclear Signal Transduction via an Endosomal Compartment
Miączyńska, M., Christoforidis, S., Giner, A., Shevchenko, A., Uttenweiler‐Joseph, S., Habermann, B. H., Wilm, M. S., Parton, R. G., & Zerial, M. (2004) · Cell · doi:10.1016/s0092-8674(04)00117-5 · Cited by 553
Friedman, L., & Kolter, R. (2004) · Journal of Bacteriology · doi:10.1128/jb.186.14.4457-4465.2004 · Cited by 528
“transmembrane domains of the predicted proteins (10, 18).”
BackgroundHigh-throughput prediction of protein antigenicity using protein microarray data
Magnan, C. N., Zeller, M. D., Kayala, M. A., Vigil, A., Randall, A. Z., Felgner, P. L., & Baldi, P. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq551 · Cited by 537
“, 1990), GCG (Accelrys Software Inc, 2005), FASTA (Pearson, 1990) and PSORT (Nakai and Horton, 1999) to predict features typical of surface-associated proteins.”
BackgroundMethodComparative Genomics of Foot-and-Mouth Disease Virus
Carrillo, C., Tulman, E. R., Delhon, G. A., Lu, Z., Carreno, A., Vagnozzi, A. E., Kutish, G. F., & Rock, D. L. (2005) · Journal of Virology · doi:10.1128/jvi.79.10.6487-6504.2005 · Cited by 505
“Transmembrane protein segment predictions were performed by using Memsat (50), Tmpred (41), Toppred (114), Psort (76), and Saps (11).”
MethodCytoglobin: A Novel Globin Type Ubiquitously Expressed inVertebrate Tissues
Burmester, T., Ebner, B., Weich, B., & Hankeln, T. (2002) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a004096 · Cited by 496
Role for Human SIRT2 NAD-Dependent Deacetylase Activity in Control of Mitotic Exit in the Cell Cycle
Dryden, S. C., Nahhas, F. A., Nowak, J. E., Goustin, A. S., & Tainsky, M. A. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.23.9.3173-3185.2003 · Cited by 506
“An analysis of amino acid motifs for protein sorting and trafficking by using the P-SORT-II algorithms based on the k-nearest neighbors classifier (28) predicts that SIRT2 would be cytoplasmic in localization (Table 1), consistent with experimental data (Fig.”
MethodThe Genome of Naegleria gruberi Illuminates Early Eukaryotic Versatility
Fritz‐Laylin, L. K., Prochnik, S. E., Ginger, M. L., Dacks, J. B., Carpenter, M. L., Field, M. C., Kuo, A., Paredez, A. R., Chapman, J., Pham, J. K., et al. (2010) · Cell · doi:10.1016/j.cell.2010.01.032 · Cited by 472
REVIEW : Recent advances in developing web-servers for predicting protein attributes
Chou, K., & Shen, H. (2009) · Natural Science · doi:10.4236/ns.2009.12011 · Cited by 463
“, [6-48] and the relevant references cited in a recent review paper [49].”
BackgroundHaustorially Expressed Secreted Proteins from Flax Rust Are Highly Enriched for Avirulence Elicitors
Catanzariti, A., Dodds, P. N., Lawrence, G. J., Ayliffe, M., & Ellis, J. G. (2005) · The Plant Cell · doi:10.1105/tpc.105.035980 · Cited by 456
“…protein sequences for each of the haustorially expressed secreted proteins (HESPs) were also entered into other signal peptide–predicting software. iPSORT (Bannai et al., 2002) predicted 17 of 20 proteins to be secreted, and PSORTII (Nakai and Horton, 1999) predicted 19 of 20 with McGeoch’s method.”
BackgroundMethodMa, X. X., Ito, T., Tiensasitorn, C., Jamklang, M., Chongtrakool, P., Boyle-Vavra, S., Daum, R. S., & Hiramatsu, K. (2002) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.46.4.1147-1152.2002 · Cited by 587
“The BLAST and MOTIF programs failed to assign any biological functions to the hypothetical ORFs in the L-C regions of type IV SCCmec elements (1, 17 ).”
BackgroundProteomics of the Chloroplast Envelope Membranes from Arabidopsis thaliana
Ferro, M., Salvi, D., Brugière, S., Miras, S., Kowalski, S., Louwagie, M., Garin, J., Joyard, J., & Rolland, N. (2003) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m300030-mcp200 · Cited by 454
“predict localization (27, 113), and ii) the integrity of thylakoids”
BackgroundPrediction of Potential GPI-modification Sites in Proprotein Sequences
Eisenhaber, B., Peer Bork, B., & Eisenhaber, F. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3069 · Cited by 443
Schmülling, T., Werner, T., Riefler, M., et al. (2003) · Journal of Plant Research · doi:10.1007/s10265-003-0096-4 · Cited by 441
“Using the TargetP (Emanuelsson et al. 2000) and PSORT programs (Nakai and Horton 1999), the majority of the Arabidopsis proteins (AtCKX2, AtCKX4, AtCKX5, AtCKX6), four of the five annotated OsCKX proteins, as well as ZmCKX1, HvCKX1, and DsCKX1 carry N-terminal sequences typical of secretion pathway…”
BackgroundMethodTwo-Component Signal Transduction Pathways in Arabidopsis
Hwang, I., Chen, H.-C., & Sheen, J. (2002) · PLANT PHYSIOLOGY · doi:10.1104/pp.005504 · Cited by 441
“Based on the analysis using the PSORT program (Nakai and Horton, 1999), AHK2, AHK3, and CRE1/AHK4/WOL are probably localized to the plasma membrane (Inoue et al., 2001; Ueguchi et al., 2001).”
MethodA cannabinoid link between mitochondria and memory
Hebert-Chatelain, E., Desprez, T., Serrat, R., Bellocchio, L., Soria-Gomez, E., Busquets-Garcia, A., Pagano Zottola, A. C., Delamarre, A., Cannich, A., Vincent, P., et al. (2016) · Nature · doi:10.1038/nature20127 · Cited by 434
PSORT-B: improving protein subcellular localization prediction for Gram-negative bacteria
Gardy, J. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg602 · Cited by 425
“Since 1991, several automated subcellular localization predictors have been developed and made available online, including: PSORT (PSORT I) for prokaryotic organisms (3), PSORT II ( 4 ), iPSORT (5) and TargetP (6) for eukaryotic organisms, and NNPSL (7) and SubLoc (8) for both organism classes.”
MethodSome remarks on predicting multi-label attributes in molecular biosystems
Chou, K. (2013) · Molecular BioSystems · doi:10.1039/c3mb25555g · Cited by 413
Molecular basis for specificity of nuclear import and prediction of nuclear localization
Marfori, M., Mynott, A. V., Ellis, J. J., Mehdi, A. M., Saunders, N. F. W., Curmi, P. M. G., Forwood, J. K., Mikael Bodén, A., & Kobe, B. (2010) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2010.10.013 · Cited by 407
“Kosugi and colleagues [63] specifically compared the predictions of their predictor with two other NLS-based predictors, PredictNLS [136] and PSORT II [142], on selected synthetic peptide libraries with measured Impα affinity (both positive and negative).”
Li, Y.-H., Qian, Q., Zhou, Y.-H., Yan, M., Sun, L., Zhang, M., Fu, Z.-M., Wang, Y.-H., Han, B., Pang, X., et al. (2003) · The Plant Cell Online · doi:10.1105/tpc.011775 · Cited by 383
“Based on hydrophobicity analysis using a method described by Kyte and Doolittle (1982), BC1 has a hydrophobic N-terminal signal peptide and a highly hydrophobic peptide at its C terminus and is predicted to be GPI anchored based on the big-PI Predictor (Eisenhaber et al., 2000) and PSORT (Nakai and Horton, 1999) progr…”
MethodInfluentialLiu, T., Song, T., Zhang, X., Yuan, H., Su, L., Li, W., Xu, J., Liu, S., Chen, L., Chen, T., et al. (2014) · Nature Communications · doi:10.1038/ncomms5686 · Cited by 406
Johnson, K. L., Jones, B. J., Bacic, A., & Schultz, C. J. (2003) · PLANT PHYSIOLOGY · doi:10.1104/pp.103.031237 · Cited by 393
“SignalP (www.cbs.dtu.dk/services/SignalP/ #submission) was used to determine the predicted length of the N-terminal signal sequence (Nielsen et al., 1997; Schultz et al., 2002).”
MethodClusterin in Alzheimer’s Disease: Mechanisms, Genetics, and Lessons From Other Pathologies
Foster, E. M., Dangla-Valls, A., Lovestone, S., Ribe, E. M., & Buckley, N. J. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00164 · Cited by 381
Induction of protein-protein interactions in live cells using light
Yazawa, M., Sadaghiani, A. M., Hsueh, B., & Dolmetsch, R. E. (2009) · Nature Biotechnology · doi:10.1038/nbt.1569 · Cited by 377
“Because nuclear localization is undesirable in a general-purpose protein interaction system, we used the PSORT II prediction progra”
MethodSchaffer, R. J., Friel, E. N., Souleyre, E. J. F., et al. (2007) · PLANT PHYSIOLOGY · doi:10.1104/pp.106.093765 · Cited by 377
“Nat Genet 38: 948–952 Nakai K, Horton P (1999) PSORT: a program for detecting the sorting signals of proteins and predicting their subcellular localization.”
MethodNLRs at the intersection of cell death and immunity
Ting, J. P.-Y., Willingham, S. B., & Bergstralh, D. T. (2008) · Nature Reviews Immunology · doi:10.1038/nri2296 · Cited by 371
Isolation and characterization of a dual-substrate phosphodiesterase gene family: PDE10A
Soderling, S. H., Bayuga, S. J., & Beavo, J. A. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.12.7071 · Cited by 374
Prp8 protein: At the heart of the spliceosome
Grainger, R. J. R., & Beggs, J. D. (2005) · RNA · doi:10.1261/rna.2220705 · Cited by 374
“Using the algorithm of Nakai (Nakai and Horton 1999), putative bipartite nuclear localization signals (NLS) are identifiable within 500 amino acids of the N terminus of Prp8 in all organisms.”
BackgroundMethodInfluentialAssessment of prediction accuracy of protein function from protein–protein interaction data
Hishigaki, H., Nakai, K., Ono, T., Tanigami, A., & Takagi, T. (2001) · Yeast · doi:10.1002/yea.706 · Cited by 358
“The prediction result of subcellular localization by PSORT (Nakai and Horton, 1999) is also shown.”
BackgroundMethodInfluentialSelf-citationFailure to produce mitochondrial DNA results in embryonic lethality in Rnaseh1 null mice
Cerritelli, S. M., Frolova, E. G., Feng, C., Grinberg, A., Love, P. E., & Crouch, R. J. (2003) · Molecular Cell · doi:10.1016/s1097-2765(03)00088-1 · Cited by 358
NucPred—Predicting nuclear localization of proteins
Brameier, M., Krings, A., & MacCallum, R. M. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm066 · Cited by 359
&cestflwr; The Hsp90 family of proteins in Arabidopsis thaliana
Krishna, P., & Gloor, G. B. (2001) · Cell Stress and Chaperones · doi:10.1379/1466-1268(2001)006 · Cited by 360
Greer, S. P., Wen, M., Bird, D. A., et al. (2007) · PLANT PHYSIOLOGY · doi:10.1104/pp.107.107300 · Cited by 357
“Vol. 145, 2007 661 SignalP 3.0 with defaults; Bendtsen et al., 2004; Emanuelsson et al., 2007) with secretory/ER targeting (TargetP 1.1 5 0.970; WoLF PSORT 5 5.0 with defaults; Nakai and Horton, 1999; Bendtsen et al., 2004; Emanuelsson et al., 2007).”
BackgroundInfluentialOtera, H., Ohsakaya, S., Nagaura, Z.-I., Ishihara, N., & Mihara, K. (2005) · The EMBO Journal · doi:10.1038/sj.emboj.7600614 · Cited by 354
“The PSORT II program (Nakai and Horton, 1999) predicts that the 17-amino-acid region between positions 67 and 83 of the AIF precursor functions as the TMS.”
MethodPeltier, J., Friso, G., Kalume, D. E., Roepstorff, P., Nilsson, F., Adamska, I., & van Wijka, K. J. (2000) · The Plant Cell · doi:10.1105/tpc.12.3.319 · Cited by 356
“The presequences of these nuclear-encoded chloroplast proteins share common features, which can be used to predict localization with moderate confidence (Emanuelsson et al., 1999; Nakai and Horton, 1999).”
BackgroundMethodInfluentialWizemann, T. M., Heinrichs, J. H., Adamou, J. E., Erwin, A. L., KUNSCH, C. A., Choi, G. H., Barash, S. C., Rosen, C. A., Masure, H. R., TUOMANEN, E. I., et al. (2001) · Infection and Immunity · doi:10.1128/iai.69.3.1593-1598.2001 · Cited by 351
“The products of 108 of these ORFs, comprising 97 unique genes or their subfragments, were successfully expressed and purified for evaluation as vaccine a Amino acid sequences are represented by single-letter designations; “X” indicates any amino acid; any amino acid in parentheses may occupy the position indicated. b…”
MethodChou, K., & Shen, H. (2010) · Natural Science · doi:10.4236/ns.2010.210136 · Cited by 348
“, [4-59].”
Teufel, M., Saudek, V., Ledig, J.-P., Bernhardt, A., Boularand, S., Carreau, A., Cairns, N. J., Carter, C. J., Cowley, D. J., Duverger, D., et al. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m209764200 · Cited by 346
Strong, W. B., Gut, J., & Nelson, R. G. (2000) · Infection and Immunity · doi:10.1128/iai.68.7.4117-4134.2000 · Cited by 343
“The amino terminus of the sequence contained a string of hydrophobic and hydroxylic amino acid residues that were predicted by the PSORT II program (57) to constitute an N-terminal signal sequence with a signal peptidase cleavage site between amino acids Ser19 and Ala20; similarly, the hydrophobic C terminus of the se…”
BackgroundBaCelLo: a balanced subcellular localization predictor
Pierleoni, A., Martelli, P. L., Fariselli, P., & Casadio, R. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl222 · Cited by 338
“…others discriminate among four classes in animals and five classes in plants and are Loctree, SubLoc, ESLpred and LOCSVMpsi. pTARGET and Psort II (Nakai and Horton, 1999) discriminate more classes than BaCelLo does, however we did not consider these classes since very few redundant examples are…”
BackgroundA Proteomics Dissection of Arabidopsis thaliana Vacuoles Isolated from Cell Culture
Jaquinod, M., Villiers, F., Kieffer‐Jaquinod, S., Hugouvieux, V., Bruley, C., Garin, J., & Bourguignon, J. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m600250-mcp200 · Cited by 346
“Complementary information was obtained using the Psort II prediction program (54).”
MethodChou, K., Wu, Z., & Xiao, X. (2011) · Molecular BioSystems · doi:10.1039/c1mb05420a · Cited by 334
Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones
Imanishi, T., Itoh, T., Suzuki, Y., O’Donovan, C., Fukuchi, S., Koyanagi, K. O., Barrero, R. A., Tamura, T., Yamaguchi‐Kabata, Y., Tanino, M., et al. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020162 · Cited by 331
“Subcellular localization targeting signals and transmembrane helices of 40,352 H-Inv proteins were predicted using the PSORT II (Nakai and Horton 1999), TargetP (Emanuelsson et al.”
Höglund, A., Dönnes, P., Blum, T., Adolph, H., & Kohlbacher, O. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl002 · Cited by 325
“The most comprehensive prediction system reported so far, PSORT, is based on a collection of expert if-then rules originating from experimental and computational observations (Nakai & Kanehisa, 1992; Nakai & Horton, 1999).”
BackgroundResultInfluentialProtein sorting signals and prediction of subcellular localization
Nakai, K. (2000) · Advances in protein chemistry · doi:10.1016/s0065-3233(00)54009-1 · Cited by 320
Self-citationLeahy, S. C., Kelly, W. J., Altermann, E., Ronimus, R. S., Yeoman, C. J., Pacheco, D. M., Li, D., Kong, Z., McTavish, S. M., Sang, C., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0008926 · Cited by 318
“) was used for the prediction of transmembrane domains and PSORT”
MethodChou, K., & Shen, H. (2007) · Journal of Proteome Research · doi:10.1021/pr060635i · Cited by 319
“The predictor obtained through the above modified procedures is called Euk-mPLoc (i) that Figure 1. Schematic illustration to show the 22 subcellular locations of eukaryotic proteins: (1) acrosome, (2) cell wall, (3) centriole, (4) chloroplast, (5) cyanelle, ( 6 ) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum…”
Prediction of Human Protein Function from Post-translational Modifications and Localization Features
Jensen, L. J., Gupta, R., Blom, N., Devos, D. P., Tamames, J., Keşmir, C., Nielsen, H., Stærfeldt, H., Rapacki, K., Workman, C. T., et al. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00379-0 · Cited by 317
“As several predictive methods for PTMs have been constructed (R.G., S.B., unpublished results), 10–13 a function prediction method based on such attributes can be applied to all proteins where the sequence is known.”
MethodPiotrowski, A., Xie, J., Liu, Y. F., Poplawski, A. B., Gomes, A., Madanecki, P., Fu, C., Crowley, M. R., Crossman, D. K., Armstrong, L., et al. (2013) · Nature Genetics · doi:10.1038/ng.2855 · Cited by 326
Kawasaki, K., & Weiss, K. M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0638023100 · Cited by 314
Getting to the roots of parasitism by nematodes
Davis, E. (2004) · Trends in Parasitology · doi:10.1016/j.pt.2004.01.005 · Cited by 317
Adenosine Kinase: Exploitation for Therapeutic Gain
Boison, D. (2013) · Pharmacological Reviews · doi:10.1124/pr.112.006361 · Cited by 320
“Founded on algorithms that predict subcellular localization based on sequence similarities, it was initially speculated that both isoforms of ADK are located in the cytoplasm (Nakai and Horton, 1999; Sakowicz et al., 2001).”
BackgroundBhasin, M., & Raghava, G. P. S. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh350 · Cited by 310
“Thepredictionaccuracyforeukaryoticproteinswas (9).”
Oegema, K., Savoian, M. S., Mitchison, T. J., & Field, C. M. (2000) · The Journal of Cell Biology · doi:10.1083/jcb.150.3.539 · Cited by 309
“The locations of potential nuclear localization sequences, identified using the program PSORT II ( Nakai and Horton, 1999 ), are indicated with black triangles (human, amino acids 64, 66, 195, 786, 896, and 1,021; Drosophila, amino acids 996 and 1,105).”
MethodIto, S., Kinoshita, S., Shiraishi, N., Nakagawa, S., Sekine, S., Fujimori, T., & Nabeshima, Y. (2000) · Mechanisms of Development · doi:10.1016/s0925-4773(00)00439-1 · Cited by 312
“Using the protein sorting prediction program (PSORTII; Nakai and Horton, 1999), we determined that like KL, bKL possesses a putative signal sequence at its Nterminus and a membrane-spanning region with short hydrophilic tail at the C-terminus.”
Mutations in PMR5 result in powdery mildew resistance and altered cell wall composition
Vogel, J. P., Raab, T. K., Somerville, C. R., & Somerville, S. C. (2004) · The Plant Journal · doi:10.1111/j.1365-313x.2004.02264.x · Cited by 300
“The first 22 aa of PMR5 are predicted to serve as a non-cleavable signal sequence that targets the protein to the endoplasmic reticulum (Target P: Olof et al., 2000; PSORT: Nakai and Horton, 1999; ProtFun 1.1: Jensen et al., 2002).”
BackgroundInfluentialCauwe, B., & Opdenakker, G. (2010) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.3109/10409238.2010.501783 · Cited by 298
“Using the bioinformatics software PSORT (Nakai and Horton, 1999), they detected a putative NLS (PKWRKTH) at position 107 to 113 in the catalytical domain, which was well conserved between the human, mouse and rat sequences of MMP-3.”
MethodAcetyl-CoA Synthetase 2, a Mitochondrial Matrix Enzyme Involved in the Oxidation of Acetate
Fujino, T., Kondo, J., Ishikawa, M., Morikawa, K., & Yamamoto, T. T. (2001) · Journal of Biological Chemistry · doi:10.1074/jbc.m008782200 · Cited by 298
Protein Transport into Chloroplasts
Li, H., & Chiu, C.-C. (2010) · Annual Review of Plant Biology · doi:10.1146/annurev-arplant-042809-112222 · Cited by 296
Mimicking Cellular Sorting Improves Prediction of Subcellular Localization
Nair, R. P., & Rost, B. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.02.025 · Cited by 290
“Comparison with other methods using additional test sets Other methods tested on new data set We compared our method to the following publicly available methods: TargetP, 33 SubLoc, 67 NNPSL, 40 and PSORT II.”
MethodXiao, X., Wu, Z.-C., & Chou, K. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020592 · Cited by 284
“They are called ‘‘PSORT’’ [1,3,4], ‘‘PSORT-B’’ [5], and PSORTb v.”
Identification of a Protein from Rust Fungi Transferred from Haustoria into Infected Plant Cells
Kemen, E. M., Kemen, A. C., Rafiqi, M., Hempel, U., Mendgen, K. W., Hahn, M., & Voegele, R. T. (2005) · Molecular Plant-Microbe Interactions · doi:10.1094/mpmi-18-1130 · Cited by 296
“AUTHOR-RECOMMENDED INTERNET RESOURCES PSORTII: psort.ims.u-tokyo.ac.jp/form2.html SignalP V2.”
The Parasitome of the Phytonematode Heterodera glycines
Gao, B., Allen, R., Maier, T. R., Davis, E., Baum, T. J., & HUSSEY, R. S. (2003) · Molecular Plant-Microbe Interactions · doi:10.1094/mpmi.2003.16.8.720 · Cited by 282
“Transmembrane regions and subcellular localization sites of the deduced proteins were predicted by TMHMM (Krogh et al. 2001) and PSORT II (Nakai and Horton 1999), respectively.”
MethodDiverse Targets of Phytoplasma Effectors: From Plant Development to Defense Against Insects
Sugio, A., MacLean, A. M., Kingdom, H. N., Grieve, V. M., Manimekalai, R., & Hogenhout, S. A. (2011) · Annual Review of Phytopathology · doi:10.1146/annurev-phyto-072910-095323 · Cited by 290
“PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization.”
BackgroundTransgene and Transposon Silencing in Chlamydomonas reinhardtii by a DEAH-Box RNA Helicase
Wu‐Scharf, D., Jeong, B., Zhang, C. H., & Cerutti, H. D. (2000) · Science · doi:10.1126/science.290.5494.1159 · Cited by 280
Quantitative Proteomic Comparison of Rat Mitochondria from Muscle, Heart, and Liver
Forner, F., Foster, L. J., Campanaro, S., Valle, G., & Mann, M. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500298-mcp200 · Cited by 280
“Mitopred or PSORT II (39), such as acid phosphatase 6 (with”
Peroxisome targeting signal 1: Is it really a simple tripeptide?
Brocard, C., & Hartig, A. (2006) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2006.08.022 · Cited by 278
“In Table 1 the PTS1-predictor is compared with the established PSORTII [69].”
Method
Metadata
- Authors
- Nakai, K., & Horton, P.
- Affiliations
- The University of Osaka (JP)
- Corresponding author
- Nakai, Kenta
- Venue
- Trends in Biochemical Sciences
- Publisher
- Elsevier BV
- Published
- 1999-01
- Volume
- 24
- Issue
- 1
- Pages
- 34-35
- ISSN
- 0968-0004 (ISSN-L)
- OpenAlex
- W2006211612
- Cited by
- 2,181
- References
- 13
- Citations by year
- 2026: 25 · 2025: 26 · 2024: 43 · 2023: 33 · 2022: 23 · 2021: 31 · 2020: 36 · 2019: 53 · 2018: 59 · 2017: 46 · 2016: 59 · 2015: 69 · 2014: 76 · 2013: 89 · 2012: 105
- FWCI
- 27.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Biochemical Sciences (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- protein sorting signals, subcellular localization prediction, protein localization, signal peptide, amino acid composition, protein function prediction
- MeSH terms
- Algorithms, Proteins, Software, Subcellular Fractions, Protein Sorting Signals
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