Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity
Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experime...
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| Published in: | Amino acids Vol. 34; no. 1; pp. 111 - 117 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Vienna
Vienna : Springer-Verlag
2008
Springer-Verlag Springer Nature B.V |
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| ISSN: | 0939-4451, 1438-2199, 1438-2199 |
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| Abstract | Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both α-helical and β-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn. |
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| AbstractList | Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both alpha-helical and beta-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn.Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both alpha-helical and beta-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn. Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both α-helical and β-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn. Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both alpha-helical and beta-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn. Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both alpha -helical and beta -barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at limlcu.edu.cn. |
| Author | Wen, Z Yin, J Li, M Xiang, J Diao, Y Ma, D |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/17520325$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1002/bip.20640 10.1016/j.jtbi.2006.05.006 10.1002/jcb.20879 10.1093/protein/gzl053 10.1007/s00726-004-0154-9 10.1093/bioinformatics/bth466 10.1002/jcb.10790 10.1002/pro.5560050824 10.1038/2983 10.1093/protein/gzh061 10.1016/j.jtbi.2004.11.017 10.1023/A:1025350409648 10.1002/prot.1071 10.3109/10409239509083488 10.1021/pr050087t 10.1016/j.jtbi.2006.06.014 10.1038/350130a0 10.1093/bioinformatics/bth054 10.1016/j.ab.2006.07.022 10.1002/prot.1035 10.1016/j.bbrc.2005.08.160 10.1093/bioinformatics/bti784 10.1016/0022-2836(82)90515-0 10.1016/j.bbrc.2005.06.087 10.1093/protein/12.2.107 10.2174/1389203003381379 10.1093/nar/22.22.4673 10.1006/bbrc.2000.3815 10.1016/j.jtbi.2006.06.025 10.1007/s00726-004-0148-7 10.1186/1471-2105-7-518 10.1038/311419a0 10.1016/j.bbrc.2006.06.059 10.1016/j.bbrc.2004.08.113 10.1007/s00726-006-0263-8 10.1002/(SICI)1097-0134(19980401)31:1<97::AID-PROT8>3.0.CO;2-E 10.1006/abio.2000.4757 10.1002/jcc.20354 10.1002/prot.340210406 10.1093/bioinformatics/btl170 10.1074/jbc.M204161200 10.1016/j.bbrc.2004.06.073 10.1007/BF01223745 10.1016/S0022-2836(05)80193-7 10.1110/ps.0305103 10.1002/jcc.10411 10.1016/j.febslet.2005.05.021 10.1006/jmbi.1998.2107 10.1002/prot.10251 10.1016/j.compbiolchem.2006.08.003 10.1023/A:1020713915365 10.1016/j.jtbi.2005.08.016 10.1002/prot.10500 10.1007/s00726-005-0225-6 10.1002/jcb.10719 10.1109/TIT.1976.1055501 10.1093/nar/gkh417 10.1007/BF01021083 10.1007/s00726-006-0341-y 10.1093/bioinformatics/bti104 10.1016/j.bbrc.2004.07.059 10.1021/pr060167c 10.1002/j.1460-2075.1986.tb04601.x 10.1016/j.bbrc.2005.09.117 10.1016/S0021-9258(17)31748-9 10.1007/s00726-006-0476-x |
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| Keywords | Keywords: Cellular automata – Pseudo amino acid composition – Lempel-Ziv complexity – Augmented covariant-discriminant algorithm – Chou’s invariance theorem – Transmembrane regions |
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| References | Chou (CR12) 1995; 21 Cai, Chou (CR3) 2004b; 20 Chou, Cai (CR19) 2002; 277 Chou, Cai (CR20) 2003a; 53 Tusnady, Simon (CR51) 1998; 283 CR35 Wen, Li, Li, Guo, Wang (CR56) 2006; 32 Chou, Elrod (CR14) 1999; 12 Zhou, Doctor (CR68) 2003; 50 Rost, Fariselli, Casadio (CR43) 1996; 5 Chou, Cai (CR23) 2004b; 91 Zhou (CR66) 1998; 17 Martin, Odlyzko, Wolfram (CR39) 1984; 93 Kyte, Doolittle (CR36) 1982; 157 Wang, Yang, Liu, Xu, Chou (CR54) 2004; 17 Du, Li (CR31) 2006; 7 Shen, Chou (CR47) 2006a; 22 Shen, Yang, Chou (CR46) 2006; 240 Bagos, Liakopoulos, Spyropoulas, Hamodrakas (CR1) 2004; 32 Chou (CR27) 2005b; 4 Chou (CR15) 2000a; 278 Xiao, Shao, Ding, Huang, Chou (CR60) 2005b; 28 Chou (CR16) 2000b; 1 Zheng, John (CR65) 2004; 25 Zhang, Ding, Chou (CR64) 2006b; 30 Xiao, Shao, Ding, Huang, Chou (CR61) 2006a; 30 Chou (CR26) 2005a; 21 Wolfram (CR57) 1984; 311 Pan, Zhang, Guo, He (CR41) 2003; 22 Chou, Zhang (CR10) 1994; 269 Chen, Tian, Zou, Cai (CR7) 2006a; 243 Thompson, Higgins, Gibson (CR50) 1994; 22 Liu, Wang, Chou (CR38) 2005; 336 Chou, Carlacci, Maggiora (CR9) 1990; 213 Chou, Shen (CR29) 2006b; 347 Cai, Zhou, Chou (CR4) 2005; 234 Gao, Wang, Yan, Du (CR32) 2005; 579 Xiao, Shao, Ding, Huang, Chou (CR59) 2005a; 28 Shen, Chou (CR49) 2007; 20 Chou, Cai (CR22) 2004a; 321 Xiao, Shao, Huang, Chou (CR62) 2006b; 27 Zhang, Pan, Zhang, Shi (CR63) 2006a; 30 Lempel, Ziv (CR37) 1976; 22 Chou (CR18) 2001; 43 Chou, Liu, Maggiora, Zhang (CR13) 1998; 31 Shen, Chou (CR44) 2005a; 337 CR53 Chen, Rost (CR6) 2002; 1 Zhou, Assa-Munt (CR67) 2001; 44 Pautsch, Schultz (CR42) 1998; 5 Chou, Cai (CR21) 2003b; 90 Mondal, Bhavna, Mohan, Ramakumar (CR40) 2006; 243 Chen, Zhou, Tian, Zou, Cai (CR8) 2006b; 357 Zhou, Zhou (CR69) 2003; 12 Chou, Zhang (CR11) 1995; 30 Chou, Cai (CR25) 2005; 21 Cao, Porollo, Adamczak, Jarrell, Meller (CR5) 2006; 22 Chou, Shen (CR28) 2006a; 99 Wolfram (CR58) 1986; 45 Cai, Chou (CR2) 2004a; 323 Chou (CR17) 2000c; 286 Chou, Cai (CR24) 2004c; 320 Hofmann, Stoffel (CR33) 1993; 374 Shen, Chou (CR45) 2005b; 334 Wang, Yang, Chou (CR55) 2006; 242 Chou, Shen (CR30) 2006c; 5 Shen, Chou (CR48) 2006b; 85 von Heijine (CR52) 1986; 5 Kuhlbrandt, Wang (CR34) 1994; 350 S Mondal (550_CR40) 2006; 243 HB Shen (550_CR44) 2005a; 337 KC Chou (550_CR15) 2000a; 278 KC Chou (550_CR11) 1995; 30 KC Chou (550_CR25) 2005; 21 KC Chou (550_CR10) 1994; 269 JD Thompson (550_CR50) 1994; 22 KC Chou (550_CR13) 1998; 31 SQ Wang (550_CR55) 2006; 242 KC Chou (550_CR16) 2000b; 1 550_CR53 KC Chou (550_CR19) 2002; 277 GP Zhou (550_CR68) 2003; 50 KC Chou (550_CR20) 2003a; 53 HB Shen (550_CR46) 2006; 240 S Wolfram (550_CR58) 1986; 45 YD Cai (550_CR4) 2005; 234 KC Chou (550_CR14) 1999; 12 X Xiao (550_CR62) 2006b; 27 KC Chou (550_CR21) 2003b; 90 KC Chou (550_CR27) 2005b; 4 HB Shen (550_CR49) 2007; 20 KC Chou (550_CR23) 2004b; 91 A Pautsch (550_CR42) 1998; 5 X Xiao (550_CR61) 2006a; 30 M Wang (550_CR54) 2004; 17 QB Gao (550_CR32) 2005; 579 KC Chou (550_CR26) 2005a; 21 T Zhang (550_CR64) 2006b; 30 C Chen (550_CR7) 2006a; 243 W Kuhlbrandt (550_CR34) 1994; 350 X Xiao (550_CR60) 2005b; 28 KC Chou (550_CR12) 1995; 21 A Lempel (550_CR37) 1976; 22 YX Pan (550_CR41) 2003; 22 GP Zhou (550_CR66) 1998; 17 GP Zhou (550_CR67) 2001; 44 J Kyte (550_CR36) 1982; 157 HY Zhou (550_CR69) 2003; 12 X Xiao (550_CR59) 2005a; 28 PG Bagos (550_CR1) 2004; 32 BQ Cao (550_CR5) 2006; 22 O Martin (550_CR39) 1984; 93 SW Zhang (550_CR63) 2006a; 30 KC Chou (550_CR9) 1990; 213 YD Cai (550_CR2) 2004a; 323 HB Shen (550_CR47) 2006a; 22 K Hofmann (550_CR33) 1993; 374 KC Chou (550_CR30) 2006c; 5 KC Chou (550_CR29) 2006b; 347 KC Chou (550_CR28) 2006a; 99 KC Chou (550_CR22) 2004a; 321 Y Zheng (550_CR65) 2004; 25 H Liu (550_CR38) 2005; 336 YD Cai (550_CR3) 2004b; 20 B Rost (550_CR43) 1996; 5 Z Wen (550_CR56) 2006; 32 C Chen (550_CR8) 2006b; 357 KC Chou (550_CR24) 2004c; 320 G von Heijine (550_CR52) 1986; 5 HB Shen (550_CR48) 2006b; 85 550_CR35 P Du (550_CR31) 2006; 7 KC Chou (550_CR18) 2001; 43 GE Tusnady (550_CR51) 1998; 283 S Wolfram (550_CR57) 1984; 311 KC Chou (550_CR17) 2000c; 286 HB Shen (550_CR45) 2005b; 334 CP Chen (550_CR6) 2002; 1 |
| References_xml | – volume: 85 start-page: 233 year: 2006b end-page: 240 ident: CR48 article-title: Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells publication-title: Biopolymers doi: 10.1002/bip.20640 – volume: 242 start-page: 941 year: 2006 end-page: 946 ident: CR55 article-title: Using stacked generalization to predict membrane protein types based on pseudo amino acid composition publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.05.006 – volume: 99 start-page: 517 year: 2006a end-page: 527 ident: CR28 article-title: Predicting protein subcellular location by fusing multiple classifiers publication-title: J Cell Biochem doi: 10.1002/jcb.20879 – volume: 1 start-page: 21 year: 2002 end-page: 35 ident: CR6 article-title: State-of-the-art in membrane protein prediction publication-title: Applied Bioinformatics – volume: 20 start-page: 39 year: 2007 end-page: 46 ident: CR49 article-title: Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins publication-title: Protein Eng Des Sel doi: 10.1093/protein/gzl053 – volume: 28 start-page: 29 year: 2005b end-page: 35 ident: CR60 article-title: Using cellular automata to generate image representation for biological sequences publication-title: Amino Acids doi: 10.1007/s00726-004-0154-9 – volume: 21 start-page: 10 year: 2005a end-page: 19 ident: CR26 article-title: Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth466 – volume: 91 start-page: 1197 year: 2004b end-page: 1203 ident: CR23 article-title: Predicting subcellular localization of proteins by hybridizing functional domain composition and pseudo-amino acid composition publication-title: J Cell Biochem doi: 10.1002/jcb.10790 – ident: CR35 – volume: 5 start-page: 1704 year: 1996 end-page: 1718 ident: CR43 article-title: Topology prediction for helical transmembrane proteins at 86% accuracy publication-title: Protein Sci doi: 10.1002/pro.5560050824 – volume: 5 start-page: 1013 year: 1998 end-page: 1017 ident: CR42 article-title: Structure of the outer membrane protein A transmembrane domain publication-title: Nat Struct Biol doi: 10.1038/2983 – volume: 17 start-page: 509 year: 2004 end-page: 516 ident: CR54 article-title: Weighted-support vector machines for predicting membrane protein types based on pseudo amino acid composition publication-title: Protein Eng Des Sel doi: 10.1093/protein/gzh061 – volume: 234 start-page: 145 year: 2005 end-page: 149 ident: CR4 article-title: Predicting enzyme family classes by hybridizing gene product composition and pseudo-amino acid composition publication-title: J Theor Biol doi: 10.1016/j.jtbi.2004.11.017 – volume: 22 start-page: 395 year: 2003 end-page: 402 ident: CR41 article-title: Application of pseudo amino acid composition for predicting protein subcellular location: stochastic signal processing approach publication-title: J Protein Chem doi: 10.1023/A:1025350409648 – volume: 44 start-page: 57 year: 2001 end-page: 59 ident: CR67 article-title: Some insights into protein structural class prediction publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.1071 – volume: 30 start-page: 275 year: 1995 end-page: 349 ident: CR11 article-title: Review: prediction of protein structural classes publication-title: Crit Rev Biochem Mol Biol doi: 10.3109/10409239509083488 – volume: 269 start-page: 22014 year: 1994 end-page: 22020 ident: CR10 article-title: Predicting protein folding types by distance functions that make allowances for amino acid interactions publication-title: J Biol Chem – volume: 4 start-page: 1413 year: 2005b end-page: 1418 ident: CR27 article-title: Prediction of G-protein-coupled receptor classes publication-title: J Proteome Res doi: 10.1021/pr050087t – volume: 243 start-page: 252 year: 2006 end-page: 260 ident: CR40 article-title: Pseudo amino acid composition and multi-class support vector machines approach for conotoxin superfamily classification publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.06.014 – volume: 350 start-page: 130 year: 1994 end-page: 134 ident: CR34 article-title: Three-dimensional structure of plant light-harvesting complex determined by electron crystallography publication-title: Nature doi: 10.1038/350130a0 – volume: 20 start-page: 1151 year: 2004b end-page: 1156 ident: CR3 article-title: Predicting subcellular localization of proteins in a hybridization space publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth054 – volume: 357 start-page: 116 year: 2006b end-page: 121 ident: CR8 article-title: Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network publication-title: Anal Biochem doi: 10.1016/j.ab.2006.07.022 – volume: 43 start-page: 246 year: 2001 end-page: 255 ident: CR18 article-title: Prediction of protein cellular attributes using pseudo amino acid composition publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.1035 – volume: 336 start-page: 737 year: 2005 end-page: 739 ident: CR38 article-title: Low-frequency Fourier spectrum for predicting membrane protein types publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2005.08.160 – volume: 22 start-page: 303 year: 2006 end-page: 309 ident: CR5 article-title: Enhanced recognition of protein transmembrane domains with prediction-based structural profiles publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti784 – volume: 157 start-page: 105 year: 1982 end-page: 132 ident: CR36 article-title: A simple method for displaying the hydroparthic character of a protein publication-title: J Mol Biol doi: 10.1016/0022-2836(82)90515-0 – volume: 334 start-page: 288 year: 2005b end-page: 292 ident: CR45 article-title: Using optimized evidence-theoretic K-nearest neighbor classifier and pseudo amino acid composition to predict membrane protein types publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2005.06.087 – volume: 12 start-page: 107 year: 1999 end-page: 118 ident: CR14 article-title: Protein subcellular location prediction publication-title: Protein Eng doi: 10.1093/protein/12.2.107 – volume: 1 start-page: 171 year: 2000b end-page: 208 ident: CR16 article-title: Review: prediction of protein structural classes and subcellular locations publication-title: Curr Protein Pept Sci doi: 10.2174/1389203003381379 – volume: 22 start-page: 4673 year: 1994 end-page: 4680 ident: CR50 article-title: CLUSTALW: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice publication-title: Nucleic Acids Res doi: 10.1093/nar/22.22.4673 – volume: 278 start-page: 477 year: 2000a end-page: 483 ident: CR15 article-title: Prediction of protein subcellular locations by incorporating quasi-sequence-order effect publication-title: Biochem Biophys Res Commun doi: 10.1006/bbrc.2000.3815 – volume: 243 start-page: 444 year: 2006a end-page: 448 ident: CR7 article-title: Using pseudo-amino acid composition and support vector machine to predict protein structural class publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.06.025 – volume: 28 start-page: 57 year: 2005a end-page: 61 ident: CR59 article-title: Using complexity measure factor to predict protein subcellular location publication-title: Amino Acids doi: 10.1007/s00726-004-0148-7 – volume: 7 start-page: 518 year: 2006 ident: CR31 article-title: Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-7-518 – volume: 311 start-page: 419 year: 1984 ident: CR57 article-title: Cellular automata as models of complexity publication-title: Nature doi: 10.1038/311419a0 – volume: 347 start-page: 150 year: 2006b end-page: 157 ident: CR29 article-title: Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2006.06.059 – volume: 323 start-page: 425 year: 2004a end-page: 428 ident: CR2 article-title: Predicting 22 protein localizations in budding yeast publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.08.113 – volume: 30 start-page: 461 year: 2006a end-page: 468 ident: CR63 article-title: Prediction protein homo-oligomer types by pseudo amino acid composition: approached with an improved feature extraction and naive Bayes feature fusion publication-title: Amino Acids doi: 10.1007/s00726-006-0263-8 – volume: 31 start-page: 97 year: 1998 end-page: 103 ident: CR13 article-title: Prediction and classification of domain structural classes publication-title: Proteins Struct Funct Genet doi: 10.1002/(SICI)1097-0134(19980401)31:1<97::AID-PROT8>3.0.CO;2-E – volume: 286 start-page: 1 year: 2000c end-page: 16 ident: CR17 article-title: Review: prediction of tight turns and their types in proteins publication-title: Anal Biochem doi: 10.1006/abio.2000.4757 – volume: 27 start-page: 478 year: 2006b end-page: 482 ident: CR62 article-title: Using pseudo amino acid composition to predict protein structural classes: approached with complexity measure factor publication-title: J Comput Chem doi: 10.1002/jcc.20354 – ident: CR53 – volume: 21 start-page: 319 year: 1995 end-page: 344 ident: CR12 article-title: A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.340210406 – volume: 5 start-page: 3021 year: 1986 end-page: 3027 ident: CR52 article-title: The distribution of positively charged residues in bacterial inner membrane proteins correlates with the transmembrane topology publication-title: EMBO J – volume: 22 start-page: 1717 year: 2006a end-page: 1722 ident: CR47 article-title: Ensemble classifier for protein fold pattern recognition publication-title: Bioinformatics doi: 10.1093/bioinformatics/btl170 – volume: 277 start-page: 45765 year: 2002 end-page: 45769 ident: CR19 article-title: Using functional domain composition and support vector machines for prediction of protein subcellular location publication-title: J Biol Chem doi: 10.1074/jbc.M204161200 – volume: 320 start-page: 1236 year: 2004c end-page: 1239 ident: CR24 article-title: Prediction of protein subcellular locations by GO-FunD-PseAA predictor publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.06.073 – volume: 93 start-page: 219 year: 1984 end-page: 258 ident: CR39 article-title: Algebraic properties of cellular automata publication-title: Commun Math Phys doi: 10.1007/BF01223745 – volume: 213 start-page: 315 year: 1990 end-page: 326 ident: CR9 article-title: Conformational and geometrical properties of idealized beta-barrels in proteins publication-title: J Mol Biol doi: 10.1016/S0022-2836(05)80193-7 – volume: 12 start-page: 1547 year: 2003 end-page: 1555 ident: CR69 article-title: Predicting the topology of transmembrane helical proteins using mean burial propensity and a hidden-Markov-model-based method publication-title: Protein Sci doi: 10.1110/ps.0305103 – volume: 25 start-page: 632 year: 2004 end-page: 636 ident: CR65 article-title: SVMtm: support vector machines to predict transmembrane segments publication-title: J Comput Chem doi: 10.1002/jcc.10411 – volume: 579 start-page: 3444 year: 2005 end-page: 3448 ident: CR32 article-title: Prediction of protein subcellular location using a combined feature of sequence publication-title: FEBS Lett doi: 10.1016/j.febslet.2005.05.021 – volume: 283 start-page: 489 year: 1998 end-page: 506 ident: CR51 article-title: Principles governing amino acid composition of integral membrane proteins: application to topology prediction publication-title: J Mol Biol doi: 10.1006/jmbi.1998.2107 – volume: 50 start-page: 44 year: 2003 end-page: 48 ident: CR68 article-title: Subcellular location prediction of apoptosis proteins publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.10251 – volume: 30 start-page: 367 year: 2006b end-page: 371 ident: CR64 article-title: Prediction of protein subcellular location using hydrophobic patterns of amino acid sequence publication-title: Comput Biol Chem doi: 10.1016/j.compbiolchem.2006.08.003 – volume: 17 start-page: 729 year: 1998 end-page: 738 ident: CR66 article-title: An intriguing controversy over protein structural class prediction publication-title: J Protein Chem doi: 10.1023/A:1020713915365 – volume: 240 start-page: 9 year: 2006 end-page: 13 ident: CR46 article-title: Fuzzy KNN for predicting membrane protein types from pseudo amino acid composition publication-title: J Theor Biol doi: 10.1016/j.jtbi.2005.08.016 – volume: 374 start-page: 166 year: 1993 ident: CR33 article-title: A database of membrane spanning proteins segments publication-title: Biol Chem – volume: 337 start-page: 752 year: 2005a end-page: 756 ident: CR44 article-title: Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition publication-title: Biochem Biophys Res Commun – volume: 53 start-page: 282 year: 2003a end-page: 289 ident: CR20 article-title: Predicting protein quaternary structure by pseudo amino acid composition publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.10500 – volume: 30 start-page: 49 year: 2006a end-page: 54 ident: CR61 article-title: Using cellular automata images and pseudo amino acid composition to predict protein subcellular location publication-title: Amino Acids doi: 10.1007/s00726-005-0225-6 – volume: 90 start-page: 1250 year: 2003b end-page: 1260 ident: CR21 article-title: Prediction and classification of protein subcellular location: sequence-order effect and pseudo amino acid composition publication-title: J Cell Biochem doi: 10.1002/jcb.10719 – volume: 22 start-page: 75 year: 1976 end-page: 81 ident: CR37 article-title: On the complexity of finite sequences publication-title: IEEE Trans Inf Theory doi: 10.1109/TIT.1976.1055501 – volume: 32 start-page: W400 year: 2004 end-page: W404 ident: CR1 article-title: PRED-TMBB: a web server for predicting the topology of β-barrel outer membrane proteins publication-title: Nucleic Acids Res doi: 10.1093/nar/gkh417 – volume: 45 start-page: 471 year: 1986 ident: CR58 article-title: Cellular automaton fluid: basic theory publication-title: J Stat Phys doi: 10.1007/BF01021083 – volume: 32 start-page: 277 year: 2006 end-page: 283 ident: CR56 article-title: Delaunay triangulation with partial least squares projection to latent structures: a model for G-protein coupled receptors classification and fast structure recognition publication-title: Amino Acids doi: 10.1007/s00726-006-0341-y – volume: 21 start-page: 944 year: 2005 end-page: 950 ident: CR25 article-title: Predicting protein localization in budding yeast publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti104 – volume: 321 start-page: 1007 year: 2004a end-page: 1009 ident: CR22 article-title: Predicting protein structural class by functional domain composition publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.07.059 – volume: 5 start-page: 1888 year: 2006c end-page: 1897 ident: CR30 article-title: Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-nearest neighbor classifiers publication-title: J Proteome Res doi: 10.1021/pr060167c – volume: 1 start-page: 171 year: 2000b ident: 550_CR16 publication-title: Curr Protein Pept Sci doi: 10.2174/1389203003381379 – volume: 5 start-page: 3021 year: 1986 ident: 550_CR52 publication-title: EMBO J doi: 10.1002/j.1460-2075.1986.tb04601.x – volume: 357 start-page: 116 year: 2006b ident: 550_CR8 publication-title: Anal Biochem doi: 10.1016/j.ab.2006.07.022 – volume: 22 start-page: 303 year: 2006 ident: 550_CR5 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti784 – volume: 50 start-page: 44 year: 2003 ident: 550_CR68 publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.10251 – volume: 278 start-page: 477 year: 2000a ident: 550_CR15 publication-title: Biochem Biophys Res Commun doi: 10.1006/bbrc.2000.3815 – volume: 22 start-page: 75 year: 1976 ident: 550_CR37 publication-title: IEEE Trans Inf Theory doi: 10.1109/TIT.1976.1055501 – volume: 31 start-page: 97 year: 1998 ident: 550_CR13 publication-title: Proteins Struct Funct Genet doi: 10.1002/(SICI)1097-0134(19980401)31:1<97::AID-PROT8>3.0.CO;2-E – volume: 21 start-page: 944 year: 2005 ident: 550_CR25 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti104 – volume: 243 start-page: 252 year: 2006 ident: 550_CR40 publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.06.014 – volume: 374 start-page: 166 year: 1993 ident: 550_CR33 publication-title: Biol Chem – volume: 321 start-page: 1007 year: 2004a ident: 550_CR22 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.07.059 – volume: 347 start-page: 150 year: 2006b ident: 550_CR29 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2006.06.059 – volume: 25 start-page: 632 year: 2004 ident: 550_CR65 publication-title: J Comput Chem doi: 10.1002/jcc.10411 – volume: 5 start-page: 1888 year: 2006c ident: 550_CR30 publication-title: J Proteome Res doi: 10.1021/pr060167c – volume: 17 start-page: 509 year: 2004 ident: 550_CR54 publication-title: Protein Eng Des Sel doi: 10.1093/protein/gzh061 – volume: 7 start-page: 518 year: 2006 ident: 550_CR31 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-7-518 – volume: 334 start-page: 288 year: 2005b ident: 550_CR45 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2005.06.087 – volume: 22 start-page: 4673 year: 1994 ident: 550_CR50 publication-title: Nucleic Acids Res doi: 10.1093/nar/22.22.4673 – volume: 28 start-page: 29 year: 2005b ident: 550_CR60 publication-title: Amino Acids doi: 10.1007/s00726-004-0154-9 – volume: 28 start-page: 57 year: 2005a ident: 550_CR59 publication-title: Amino Acids doi: 10.1007/s00726-004-0148-7 – volume: 234 start-page: 145 year: 2005 ident: 550_CR4 publication-title: J Theor Biol doi: 10.1016/j.jtbi.2004.11.017 – volume: 12 start-page: 107 year: 1999 ident: 550_CR14 publication-title: Protein Eng doi: 10.1093/protein/12.2.107 – volume: 91 start-page: 1197 year: 2004b ident: 550_CR23 publication-title: J Cell Biochem doi: 10.1002/jcb.10790 – volume: 43 start-page: 246 year: 2001 ident: 550_CR18 publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.1035 – volume: 17 start-page: 729 year: 1998 ident: 550_CR66 publication-title: J Protein Chem doi: 10.1023/A:1020713915365 – volume: 157 start-page: 105 year: 1982 ident: 550_CR36 publication-title: J Mol Biol doi: 10.1016/0022-2836(82)90515-0 – volume: 32 start-page: W400 year: 2004 ident: 550_CR1 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkh417 – volume: 4 start-page: 1413 year: 2005b ident: 550_CR27 publication-title: J Proteome Res doi: 10.1021/pr050087t – volume: 27 start-page: 478 year: 2006b ident: 550_CR62 publication-title: J Comput Chem doi: 10.1002/jcc.20354 – volume: 323 start-page: 425 year: 2004a ident: 550_CR2 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.08.113 – volume: 90 start-page: 1250 year: 2003b ident: 550_CR21 publication-title: J Cell Biochem doi: 10.1002/jcb.10719 – volume: 337 start-page: 752 year: 2005a ident: 550_CR44 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2005.09.117 – volume: 30 start-page: 367 year: 2006b ident: 550_CR64 publication-title: Comput Biol Chem doi: 10.1016/j.compbiolchem.2006.08.003 – volume: 99 start-page: 517 year: 2006a ident: 550_CR28 publication-title: J Cell Biochem doi: 10.1002/jcb.20879 – volume: 30 start-page: 275 year: 1995 ident: 550_CR11 publication-title: Crit Rev Biochem Mol Biol doi: 10.3109/10409239509083488 – volume: 5 start-page: 1704 year: 1996 ident: 550_CR43 publication-title: Protein Sci doi: 10.1002/pro.5560050824 – volume: 20 start-page: 39 year: 2007 ident: 550_CR49 publication-title: Protein Eng Des Sel doi: 10.1093/protein/gzl053 – volume: 21 start-page: 10 year: 2005a ident: 550_CR26 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth466 – volume: 269 start-page: 22014 year: 1994 ident: 550_CR10 publication-title: J Biol Chem doi: 10.1016/S0021-9258(17)31748-9 – volume: 5 start-page: 1013 year: 1998 ident: 550_CR42 publication-title: Nat Struct Biol doi: 10.1038/2983 – volume: 45 start-page: 471 year: 1986 ident: 550_CR58 publication-title: J Stat Phys doi: 10.1007/BF01021083 – volume: 44 start-page: 57 year: 2001 ident: 550_CR67 publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.1071 – volume: 22 start-page: 395 year: 2003 ident: 550_CR41 publication-title: J Protein Chem doi: 10.1023/A:1025350409648 – volume: 53 start-page: 282 year: 2003a ident: 550_CR20 publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.10500 – volume: 1 start-page: 21 year: 2002 ident: 550_CR6 publication-title: Applied Bioinformatics – volume: 240 start-page: 9 year: 2006 ident: 550_CR46 publication-title: J Theor Biol doi: 10.1016/j.jtbi.2005.08.016 – volume: 243 start-page: 444 year: 2006a ident: 550_CR7 publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.06.025 – volume: 336 start-page: 737 year: 2005 ident: 550_CR38 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2005.08.160 – volume: 311 start-page: 419 year: 1984 ident: 550_CR57 publication-title: Nature doi: 10.1038/311419a0 – volume: 85 start-page: 233 year: 2006b ident: 550_CR48 publication-title: Biopolymers doi: 10.1002/bip.20640 – volume: 12 start-page: 1547 year: 2003 ident: 550_CR69 publication-title: Protein Sci doi: 10.1110/ps.0305103 – volume: 283 start-page: 489 year: 1998 ident: 550_CR51 publication-title: J Mol Biol doi: 10.1006/jmbi.1998.2107 – volume: 277 start-page: 45765 year: 2002 ident: 550_CR19 publication-title: J Biol Chem doi: 10.1074/jbc.M204161200 – volume: 213 start-page: 315 year: 1990 ident: 550_CR9 publication-title: J Mol Biol doi: 10.1016/S0022-2836(05)80193-7 – volume: 22 start-page: 1717 year: 2006a ident: 550_CR47 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btl170 – volume: 20 start-page: 1151 year: 2004b ident: 550_CR3 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth054 – ident: 550_CR35 doi: 10.1007/s00726-006-0476-x – volume: 32 start-page: 277 year: 2006 ident: 550_CR56 publication-title: Amino Acids doi: 10.1007/s00726-006-0341-y – volume: 30 start-page: 461 year: 2006a ident: 550_CR63 publication-title: Amino Acids doi: 10.1007/s00726-006-0263-8 – volume: 93 start-page: 219 year: 1984 ident: 550_CR39 publication-title: Commun Math Phys doi: 10.1007/BF01223745 – volume: 30 start-page: 49 year: 2006a ident: 550_CR61 publication-title: Amino Acids doi: 10.1007/s00726-005-0225-6 – volume: 21 start-page: 319 year: 1995 ident: 550_CR12 publication-title: Proteins Struct Funct Genet doi: 10.1002/prot.340210406 – volume: 579 start-page: 3444 year: 2005 ident: 550_CR32 publication-title: FEBS Lett doi: 10.1016/j.febslet.2005.05.021 – volume: 350 start-page: 130 year: 1994 ident: 550_CR34 publication-title: Nature doi: 10.1038/350130a0 – volume: 286 start-page: 1 year: 2000c ident: 550_CR17 publication-title: Anal Biochem doi: 10.1006/abio.2000.4757 – volume: 320 start-page: 1236 year: 2004c ident: 550_CR24 publication-title: Biochem Biophys Res Commun doi: 10.1016/j.bbrc.2004.06.073 – ident: 550_CR53 – volume: 242 start-page: 941 year: 2006 ident: 550_CR55 publication-title: J Theor Biol doi: 10.1016/j.jtbi.2006.05.006 |
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| Snippet | Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions.... Transmembrane (TM) proteins represent about 20–30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions.... |
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| SubjectTerms | Amino acid composition Amino acid sequence amino acid sequences Amino acids Amino Acids - chemistry Amino Acids - metabolism Analytical Chemistry Augmented covariant-discriminant algorithm Automata theory Biochemical Engineering Biochemistry Biomedical and Life Sciences Cellular automata Cellular structure Chou's invariance theorem Complexity Composition Computational Biology data collection drugs Eukaryotes eukaryotic cells Genetics Lempel-Ziv complexity Life Sciences Mathematical models Membrane proteins Membrane Proteins - chemistry Membrane Proteins - metabolism Membranes Models, Molecular Neurobiology prediction Protein structure Protein Structure, Secondary Protein Structure, Tertiary Proteins Proteomics Pseudo amino acid composition Sequence Analysis, Protein Source code Structure-function relationships Topology Transmembrane regions |
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| Title | Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity |
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