Solving the protein sequence metric problem

Atchley WR, Zhao J, Fernandes AD, Drüke T (2005)

Zeitschriftenaufsatz | Veröffentlicht | Englisch
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Atchley, William R.; Zhao, Jieping; Fernandes, Andrew D.; Drüke, Tanja
Abstract / Bemerkung
Biological sequences are composed of long strings of alphabetic letters rather than arrays of numerical values. Lack of a natural underlying metric for comparing such alphabetic data significantly inhibits sophisticated statistical analyses of sequences, modeling structural and functional aspects of proteins, and related problems. Herein, we use multivariate statistical analyses on almost 500 amino acid attributes to produce a small set of highly interpretable numeric patterns of amino acid variability. These high-dimensional attribute data are summarized by five multidimensional patterns of attribute covariation that reflect polarity, secondary structure, molecular volume, codon diversity, and electrostatic charge. Numerical scores for each amino acid then transform amino acid sequences for statistical analyses. Relationships between transformed data and amino acid substitution matrices show significant associations for polarity and codon diversity scores. Transformed alphabetic data are used in analysis of variance and discriminant analysis to study DNA binding in the basic helix-loop-helix proteins. The transformed scores offer a general solution for analyzing a wide variety of sequence analysis problems.
amino acid attributes; multivariate statistics; basic helix-loop-helix; molecular evolution; factor analysis
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Atchley WR, Zhao J, Fernandes AD, Drüke T. Solving the protein sequence metric problem. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 2005;102(18):6395-6400.
Atchley, W. R., Zhao, J., Fernandes, A. D., & Drüke, T. (2005). Solving the protein sequence metric problem. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 102(18), 6395-6400.
Atchley, William R., Zhao, Jieping, Fernandes, Andrew D., and Drüke, Tanja. 2005. “Solving the protein sequence metric problem”. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 102 (18): 6395-6400.
Atchley, W. R., Zhao, J., Fernandes, A. D., and Drüke, T. (2005). Solving the protein sequence metric problem. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 102, 6395-6400.
Atchley, W.R., et al., 2005. Solving the protein sequence metric problem. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 102(18), p 6395-6400.
W.R. Atchley, et al., “Solving the protein sequence metric problem”, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 102, 2005, pp. 6395-6400.
Atchley, W.R., Zhao, J., Fernandes, A.D., Drüke, T.: Solving the protein sequence metric problem. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 102, 6395-6400 (2005).
Atchley, William R., Zhao, Jieping, Fernandes, Andrew D., and Drüke, Tanja. “Solving the protein sequence metric problem”. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 102.18 (2005): 6395-6400.

154 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

An evaluation of alternative explanations for widespread cytonuclear discordance in annual sunflowers (Helianthus).
Lee-Yaw JA, Grassa CJ, Joly S, Andrew RL, Rieseberg LH., New Phytol 221(1), 2019
PMID: 30136727
Deep learning in omics: a survey and guideline.
Zhang Z, Zhao Y, Liao X, Shi W, Li K, Zou Q, Peng S., Brief Funct Genomics 18(1), 2019
PMID: 30265280
A quantitative map of protein sequence space for the cis-defensin superfamily.
Shafee T, Anderson MA., Bioinformatics 35(5), 2019
PMID: 30102339
Predicting protein residue-residue contacts using random forests and deep networks.
Luttrell J, Liu T, Zhang C, Wang Z., BMC Bioinformatics 20(suppl 2), 2019
PMID: 30871477
Scoring amino acid mutation to predict pandemic risk of avian influenza virus.
Qiang X, Kou Z., BMC Bioinformatics 20(suppl 8), 2019
PMID: 31182019
Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.
Miho E, Yermanos A, Weber CR, Berger CT, Reddy ST, Greiff V., Front Immunol 9(), 2018
PMID: 29515569
Signatures of diversifying selection and convergence acting on passerine Toll-like receptor 4 in an evolutionary context.
Králová T, Albrecht T, Bryja J, Hořák D, Johnsen A, Lifjeld JT, Novotný M, Sedláček O, Velová H, Vinkler M., Mol Ecol 27(13), 2018
PMID: 29772096
Toll-like receptor evolution in birds: gene duplication, pseudogenisation and diversifying selection.
Velová H, Gutowska-Ding MW, Burt DW, Vinkler M., Mol Biol Evol (), 2018
PMID: 29893911
RNA-protein interactions in an unstructured context.
Zagrovic B, Bartonek L, Polyansky AA., FEBS Lett 592(17), 2018
PMID: 29851074
Physicochemical sequence characteristics that influence S-palmitoylation propensity.
Reddy KD, Malipeddi J, DeForte S, Pejaver V, Radivojac P, Uversky VN, Deschenes RJ., J Biomol Struct Dyn 35(11), 2017
PMID: 27498722
PrAS: Prediction of amidation sites using multiple feature extraction.
Wang T, Zheng W, Wuyun Q, Wu Z, Ruan J, Hu G, Gao J., Comput Biol Chem 66(), 2017
PMID: 27918921
Identification of the core regulators of the HLA I-peptide binding process.
Zhang YH, Xing Z, Liu C, Wang S, Huang T, Cai YD, Kong X., Sci Rep 7(), 2017
PMID: 28211542
Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions.
Meng F, Uversky VN, Kurgan L., Cell Mol Life Sci 74(17), 2017
PMID: 28589442
PRmePRed: A protein arginine methylation prediction tool.
Kumar P, Joy J, Pandey A, Gupta D., PLoS One 12(8), 2017
PMID: 28813517
A weighted string kernel for protein fold recognition.
Nojoomi S, Koehl P., BMC Bioinformatics 18(1), 2017
PMID: 28841820
Deep learning in bioinformatics.
Min S, Lee B, Yoon S., Brief Bioinform 18(5), 2017
PMID: 27473064
HLA class I binding prediction via convolutional neural networks.
Vang YS, Xie X., Bioinformatics 33(17), 2017
PMID: 28444127
Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis.
Ostmeyer J, Christley S, Rounds WH, Toby I, Greenberg BM, Monson NL, Cowell LG., BMC Bioinformatics 18(1), 2017
PMID: 28882107
Structure-Related Differences between Cytochrome Oxidase I Proteins in a Stable Heteroplasmic Mitochondrial System.
Skibinski DOF, Ghiselli F, Diz AP, Milani L, Mullins JGL., Genome Biol Evol 9(12), 2017
PMID: 29149282
TCRβ repertoire of CD4+ and CD8+ T cells is distinct in richness, distribution, and CDR3 amino acid composition.
Li HM, Hiroi T, Zhang Y, Shi A, Chen G, De S, Metter EJ, Wood WH, Sharov A, Milner JD, Becker KG, Zhan M, Weng NP., J Leukoc Biol 99(3), 2016
PMID: 26394815
Whole-Genome Identification, Phylogeny, and Evolution of the Cytochrome P450 Family 2 (CYP2) Subfamilies in Birds.
Almeida D, Maldonado E, Khan I, Silva L, Gilbert MT, Zhang G, Jarvis ED, O'Brien SJ, Johnson WE, Antunes A., Genome Biol Evol 8(4), 2016
PMID: 26979796
Prediction of protein-protein interaction sites by means of ensemble learning and weighted feature descriptor.
Du X, Sun S, Hu C, Li X, Xia J., J Biol Res (Thessalon) 23(suppl 1), 2016
PMID: 27437195
Adaptive evolution of virus-sensing toll-like receptor 8 in bats.
Schad J, Voigt CC., Immunogenetics 68(10), 2016
PMID: 27502317
Visual Pigments, Ocular Filters and the Evolution of Snake Vision.
Simões BF, Sampaio FL, Douglas RH, Kodandaramaiah U, Casewell NR, Harrison RA, Hart NS, Partridge JC, Hunt DM, Gower DJ., Mol Biol Evol 33(10), 2016
PMID: 27535583
ASAP: a machine learning framework for local protein properties.
Brandes N, Ofer D, Linial M., Database (Oxford) 2016(), 2016
PMID: 27694209
Exploring Mouse Protein Function via Multiple Approaches.
Huang G, Chu C, Huang T, Kong X, Zhang Y, Zhang N, Cai YD., PLoS One 11(11), 2016
PMID: 27846315
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.
Spencer M, Eickholt J, Jianlin Cheng., IEEE/ACM Trans Comput Biol Bioinform 12(1), 2015
PMID: 25750595
Evolutionary pattern in the OXT-OXTR system in primates: coevolution and positive selection footprints.
Vargas-Pinilla P, Paixão-Côrtes VR, Paré P, Tovo-Rodrigues L, Vieira CM, Xavier A, Comas D, Pissinatti A, Sinigaglia M, Rigo MM, Vieira GF, Lucion AB, Salzano FM, Bortolini MC., Proc Natl Acad Sci U S A 112(1), 2015
PMID: 25535371
A method to distinguish between lysine acetylation and lysine ubiquitination with feature selection and analysis.
Zhou Y, Zhang N, Li BQ, Huang T, Cai YD, Kong XY., J Biomol Struct Dyn 33(11), 2015
PMID: 25616595
Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer.
Twyman-Saint Victor C, Rech AJ, Maity A, Rengan R, Pauken KE, Stelekati E, Benci JL, Xu B, Dada H, Odorizzi PM, Herati RS, Mansfield KD, Patsch D, Amaravadi RK, Schuchter LM, Ishwaran H, Mick R, Pryma DA, Xu X, Feldman MD, Gangadhar TC, Hahn SM, Wherry EJ, Vonderheide RH, Minn AJ., Nature 520(7547), 2015
PMID: 25754329
Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods.
Liu Y, Gu W, Zhang W, Wang J., Biomed Res Int 2015(), 2015
PMID: 25961025
Quantifying domain-ligand affinities and specificities by high-throughput holdup assay.
Vincentelli R, Luck K, Poirson J, Polanowska J, Abdat J, Blémont M, Turchetto J, Iv F, Ricquier K, Straub ML, Forster A, Cassonnet P, Borg JP, Jacob Y, Masson M, Nominé Y, Reboul J, Wolff N, Charbonnier S, Travé G., Nat Methods 12(8), 2015
PMID: 26053890
Evolution of substrate recognition sites (SRSs) in cytochromes P450 from Apiaceae exemplified by the CYP71AJ subfamily.
Dueholm B, Krieger C, Drew D, Olry A, Kamo T, Taboureau O, Weitzel C, Bourgaud F, Hehn A, Simonsen HT., BMC Evol Biol 15(), 2015
PMID: 26111527
ProFET: Feature engineering captures high-level protein functions.
Ofer D, Linial M., Bioinformatics 31(21), 2015
PMID: 26130574
Positive selection in octopus haemocyanin indicates functional links to temperature adaptation.
Oellermann M, Strugnell JM, Lieb B, Mark FC., BMC Evol Biol 15(), 2015
PMID: 26142723
Interaction preferences between nucleobase mimetics and amino acids in aqueous solutions.
Hajnic M, Osorio JI, Zagrovic B., Phys Chem Chem Phys 17(33), 2015
PMID: 26219945
PINGU: PredIction of eNzyme catalytic residues usinG seqUence information.
Pai PP, Ranjani SS, Mondal S., PLoS One 10(8), 2015
PMID: 26261982
Characterizing the Diverse Mutational Pathways Associated with R5-Tropic Maraviroc Resistance: HIV-1 That Uses the Drug-Bound CCR5 Coreceptor.
Jiang X, Feyertag F, Meehan CJ, McCormack GP, Travers SA, Craig C, Westby M, Lewis M, Robertson DL., J Virol 89(22), 2015
PMID: 26339063
Predicting DNA-binding sites of proteins based on sequential and 3D structural information.
Li BQ, Feng KY, Ding J, Cai YD., Mol Genet Genomics 289(3), 2014
PMID: 24448651
Prediction of aptamer-target interacting pairs with pseudo-amino acid composition.
Li BQ, Zhang YC, Huang GH, Cui WR, Zhang N, Cai YD., PLoS One 9(1), 2014
PMID: 24466214
Principal components analysis of protein sequence clusters.
Wang B, Kennedy MA., J Struct Funct Genomics 15(1), 2014
PMID: 24496727
Mapping the amino acid properties of constituent nucleoporins onto the yeast nuclear pore complex.
Kunda A, Krishnan NH, Krishnan V., Bioinformation 10(2), 2014
PMID: 24616561
Genetic host specificity of hepatitis E virus.
Lara J, Purdy MA, Khudyakov YE., Infect Genet Evol 24(), 2014
PMID: 24667049
Prediction of multi-type membrane proteins in human by an integrated approach.
Huang G, Zhang Y, Chen L, Zhang N, Huang T, Cai YD., PLoS One 9(3), 2014
PMID: 24676214
The elusive nature of adaptive mitochondrial DNA evolution of an arctic lineage prone to frequent introgression.
Melo-Ferreira J, Vilela J, Fonseca MM, da Fonseca RR, Boursot P, Alves PC., Genome Biol Evol 6(4), 2014
PMID: 24696399
SuSPect: enhanced prediction of single amino acid variant (SAV) phenotype using network features.
Yates CM, Filippis I, Kelley LA, Sternberg MJ., J Mol Biol 426(14), 2014
PMID: 24810707
Integration of residue attributes for sequence diversity characterization of terpenoid enzymes.
Kibinge N, Ikeda S, Ono N, Altaf-Ul-Amin M, Kanaya S., Biomed Res Int 2014(), 2014
PMID: 24900985
Understanding and identifying amino acid repeats.
Luo H, Nijveen H., Brief Bioinform 15(4), 2014
PMID: 23418055
A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.
Du X, Cheng J, Zheng T, Duan Z, Qian F., Int J Mol Sci 15(7), 2014
PMID: 25046746
Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence.
Thomas N, Best K, Cinelli M, Reich-Zeliger S, Gal H, Shifrut E, Madi A, Friedman N, Shawe-Taylor J, Chain B., Bioinformatics 30(22), 2014
PMID: 25095879
Discriminating between lysine sumoylation and lysine acetylation using mRMR feature selection and analysis.
Zhang N, Zhou Y, Huang T, Zhang YC, Li BQ, Chen L, Cai YD., PLoS One 9(9), 2014
PMID: 25222670
Relationship between Metabolic Fluxes and Sequence-Derived Properties of Enzymes.
Zikmanis P, Kampenusa I., Int Sch Res Notices 2014(), 2014
PMID: 27437461
Protein evolution of Toll-like receptors 4, 5 and 7 within Galloanserae birds.
Vinkler M, Bainová H, Bryja J., Genet Sel Evol 46(), 2014
PMID: 25387947
PCP-ML: protein characterization package for machine learning.
Eickholt J, Wang Z., BMC Res Notes 7(), 2014
PMID: 25406415
Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.
Gao YF, Li BQ, Cai YD, Feng KY, Li ZD, Jiang Y., Mol Biosyst 9(1), 2013
PMID: 23117653
Analogue encoding of physicochemical properties of proteins in their cognate messenger RNAs.
Polyansky AA, Hlevnjak M, Zagrovic B., Nat Commun 4(), 2013
PMID: 24253588
Prediction and analysis of antibody amyloidogenesis from sequences.
Liaw C, Tung CW, Ho SY., PLoS One 8(1), 2013
PMID: 23308169
DNdisorder: predicting protein disorder using boosting and deep networks.
Eickholt J, Cheng J., BMC Bioinformatics 14(), 2013
PMID: 23497251
Analysis of physicochemical and structural properties determining HIV-1 coreceptor usage.
Bozek K, Lengauer T, Sierra S, Kaiser R, Domingues FS., PLoS Comput Biol 9(3), 2013
PMID: 23555214
Bayesian factor models in characterizing molecular adaptation.
Datta S, Prado R, Rodríguez A., J Appl Stat 40(7), 2013
PMID: 26924870
Prediction of protein amidation sites by feature selection and analysis.
Cui W, Niu S, Zheng L, Hu L, Huang T, Gu L, Feng K, Zhang N, Cai Y, Li Y., Mol Genet Genomics 288(9), 2013
PMID: 23793388
Prediction and Analysis of Post-Translational Pyruvoyl Residue Modification Sites from Internal Serines in Proteins.
Jiang Y, Li BQ, Zhang Y, Feng YM, Gao YF, Zhang N, Cai YD., PLoS One 8(6), 2013
PMID: 23805260
Position-specific analysis and prediction of protein pupylation sites based on multiple features.
Zhao X, Dai J, Ning Q, Ma Z, Yin M, Sun P., Biomed Res Int 2013(), 2013
PMID: 24066285
Site selectivity for protein tyrosine nitration: insights from features of structure and topological network.
Cheng S, Lian B, Liang J, Shi T, Xie L, Zhao YL., Mol Biosyst 9(11), 2013
PMID: 24056708
Prediction of carbamylated lysine sites based on the one-class k-nearest neighbor method.
Huang G, Zhou Y, Zhang Y, Li BQ, Zhang N, Cai YD., Mol Biosyst 9(11), 2013
PMID: 24056952
Epitope predictions indicate the presence of two distinct types of epitope-antibody-reactivities determined by epitope profiling of intravenous immunoglobulins.
Luštrek M, Lorenz P, Kreutzer M, Qian Z, Steinbeck F, Wu D, Born N, Ziems B, Hecker M, Blank M, Shoenfeld Y, Cao Z, Glocker MO, Li Y, Fuellen G, Thiesen HJ., PLoS One 8(11), 2013
PMID: 24244326
Prediction of lysine ubiquitination with mRMR feature selection and analysis.
Cai Y, Huang T, Hu L, Shi X, Xie L, Li Y., Amino Acids 42(4), 2012
PMID: 21267749
Predict and analyze S-nitrosylation modification sites with the mRMR and IFS approaches.
Li BQ, Hu LL, Niu S, Cai YD, Chou KC., J Proteomics 75(5), 2012
PMID: 22178444
SySAP: a system-level predictor of deleterious single amino acid polymorphisms.
Huang T, Wang C, Zhang G, Xie L, Li Y., Protein Cell 3(1), 2012
PMID: 22183811
ESpritz: accurate and fast prediction of protein disorder.
Walsh I, Martin AJ, Di Domenico T, Tosatto SC., Bioinformatics 28(4), 2012
PMID: 22190692
Predicting protein oxidation sites with feature selection and analysis approach.
Niu S, Hu LL, Zheng LL, Huang T, Feng KY, Cai YD, Li HP, Li YX, Chou KC., J Biomol Struct Dyn 29(6), 2012
PMID: 22545996
Ab initio detection of fuzzy amino acid tandem repeats in protein sequences.
Pellegrini M, Renda ME, Vecchio A., BMC Bioinformatics 13 Suppl 3(), 2012
PMID: 22536906
Prediction of protein domain with mRMR feature selection and analysis.
Li BQ, Hu LL, Chen L, Feng KY, Cai YD, Chou KC., PLoS One 7(6), 2012
PMID: 22720092
Sequence signatures of direct complementarity between mRNAs and cognate proteins on multiple levels.
Hlevnjak M, Polyansky AA, Zagrovic B., Nucleic Acids Res 40(18), 2012
PMID: 22844092
A comparison of computational methods for identifying virulence factors.
Zheng LL, Li YX, Ding J, Guo XK, Feng KY, Wang YJ, Hu LL, Cai YD, Hao P, Chou KC., PLoS One 7(8), 2012
PMID: 22880014
Prediction of protein-protein interaction sites by random forest algorithm with mRMR and IFS.
Li BQ, Feng KY, Chen L, Huang T, Cai YD., PLoS One 7(8), 2012
PMID: 22937126
Reduced false positives in PDZ binding prediction using sequence and structural descriptors.
Hawkins JC, Zhu H, Teyra J, Pisabarro MT., IEEE/ACM Trans Comput Biol Bioinform 9(5), 2012
PMID: 22508908
Prediction of protein cleavage site with feature selection by random forest.
Li BQ, Cai YD, Feng KY, Zhao GJ., PLoS One 7(9), 2012
PMID: 23029276
Predicting protein residue-residue contacts using deep networks and boosting.
Eickholt J, Cheng J., Bioinformatics 28(23), 2012
PMID: 23047561
Proteomic properties reveal phyloecological clusters of Archaea.
Nikolic N, Smole Z, Krisko A., PLoS One 7(10), 2012
PMID: 23133575
The role of insulin C-peptide in the coevolution analyses of the insulin signaling pathway: a hint for its functions.
Wang S, Wei W, Zheng Y, Hou J, Dou Y, Zhang S, Luo X, Cai X., PLoS One 7(12), 2012
PMID: 23300796
Prediction and analysis of protein palmitoylation sites.
Hu LL, Wan SB, Niu S, Shi XH, Li HP, Cai YD, Chou KC., Biochimie 93(3), 2011
PMID: 21075167
NClassG+: A classifier for non-classically secreted Gram-positive bacterial proteins.
Restrepo-Montoya D, Pino C, Nino LF, Patarroyo ME, Patarroyo MA., BMC Bioinformatics 12(), 2011
PMID: 21235786
Proteome sequence features carry signatures of the environmental niche of prokaryotes.
Smole Z, Nikolic N, Supek F, Šmuc T, Sbalzarini IF, Krisko A., BMC Evol Biol 11(), 2011
PMID: 21269423
Prediction of antimicrobial peptides based on sequence alignment and feature selection methods.
Wang P, Hu L, Liu G, Jiang N, Chen X, Xu J, Zheng W, Li L, Tan M, Chen Z, Song H, Cai YD, Chou KC., PLoS One 6(4), 2011
PMID: 21533231
Predicting transcriptional activity of multiple site p53 mutants based on hybrid properties.
Huang T, Niu S, Xu Z, Huang Y, Kong X, Cai YD, Chou KC., PLoS One 6(8), 2011
PMID: 21857971
Evolution of the Max and Mlx networks in animals.
McFerrin LG, Atchley WR., Genome Biol Evol 3(), 2011
PMID: 21859806
The coevolution of phycobilisomes: molecular structure adapting to functional evolution.
Shi F, Qin S, Wang YC., Comp Funct Genomics 2011(), 2011
PMID: 21904470
iDNA-Prot: identification of DNA binding proteins using random forest with grey model.
Lin WZ, Fang JA, Xiao X, Chou KC., PLoS One 6(9), 2011
PMID: 21935457
Tree preserving embedding.
Shieh AD, Hashimoto TB, Airoldi EM., Proc Natl Acad Sci U S A 108(41), 2011
PMID: 21949369
First-step mutations for adaptation at elevated temperature increase capsid stability in a virus.
Lee KH, Miller CR, Nagel AC, Wichman HA, Joyce P, Ytreberg FM., PLoS One 6(9), 2011
PMID: 21980515
Classification of GPCRs using family specific motifs.
Cobanoglu MC, Saygin Y, Sezerman U., IEEE/ACM Trans Comput Biol Bioinform 8(6), 2011
PMID: 20876934
Prediction of lysine ubiquitylation with ensemble classifier and feature selection.
Zhao X, Li X, Ma Z, Yin M., Int J Mol Sci 12(12), 2011
PMID: 22272076
Prediction of deleterious non-synonymous SNPs based on protein interaction network and hybrid properties.
Huang T, Wang P, Ye ZQ, Xu H, He Z, Feng KY, Hu L, Cui W, Wang K, Dong X, Xie L, Kong X, Cai YD, Li Y., PLoS One 5(7), 2010
PMID: 20689580
ProCoS: Protein composition server.
Rishishwar L, Mishra N, Pant B, Pant K, Pardasani KR., Bioinformation 5(5), 2010
PMID: 21364804
A machine-learning approach for predicting B-cell epitopes.
Rubinstein ND, Mayrose I, Pupko T., Mol Immunol 46(5), 2009
PMID: 18947876
EFICAz2: enzyme function inference by a combined approach enhanced by machine learning.
Arakaki AK, Huang Y, Skolnick J., BMC Bioinformatics 10(), 2009
PMID: 19361344
Interpretable numerical descriptors of amino acid space.
Georgiev AG., J Comput Biol 16(5), 2009
PMID: 19432540
REPETITA: detection and discrimination of the periodicity of protein solenoid repeats by discrete Fourier transform.
Marsella L, Sirocco F, Trovato A, Seno F, Tosatto SC., Bioinformatics 25(12), 2009
PMID: 19478001
Genome scale enzyme-metabolite and drug-target interaction predictions using the signature molecular descriptor.
Faulon JL, Misra M, Martin S, Sale K, Sapra R., Bioinformatics 24(2), 2008
PMID: 18037612
Protein homology detection and fold inference through multiple alignment entropy profiles.
Sánchez-Flores A, Pérez-Rueda E, Segovia L., Proteins 70(1), 2008
PMID: 17671981
The hidden universal distribution of amino acid biosynthetic networks: a genomic perspective on their origins and evolution.
Hernández-Montes G, Díaz-Mejía JJ, Pérez-Rueda E, Segovia L., Genome Biol 9(6), 2008
PMID: 18541022
Coordinated evolution of the hepatitis C virus.
Campo DS, Dimitrova Z, Mitchell RJ, Lara J, Khudyakov Y., Proc Natl Acad Sci U S A 105(28), 2008
PMID: 18621679
Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics.
Caporaso JG, Smit S, Easton BC, Hunter L, Huttley GA, Knight R., BMC Evol Biol 8(), 2008
PMID: 19055758
Application of complex demodulation on bZIP and bHLH-PAS protein domains.
Wang Z, Smith CE, Atchley WR., Math Biosci 207(2), 2007
PMID: 17374384
Accurate prediction of deleterious protein kinase polymorphisms.
Torkamani A, Schork NJ., Bioinformatics 23(21), 2007
PMID: 17855419
Sequence comparison and protein structure prediction.
Dunbrack RL., Curr Opin Struct Biol 16(3), 2006
PMID: 16713709

27 References

Daten bereitgestellt von Europe PubMed Central.

Sequence signatures and the probabilistic identification of proteins in the Myc-Max-Mad network.
Atchley WR, Fernandes AD., Proc. Natl. Acad. Sci. U.S.A. 102(18), 2005
PMID: 15851686
Positional dependence, cliques, and predictive motifs in the bHLH protein domain.
Atchley WR, Terhalle W, Dress A., J. Mol. Evol. 48(5), 1999
PMID: 10198117
Correlations among amino acid sites in bHLH protein domains: an information theoretic analysis.
Atchley WR, Wollenberg KR, Fitch WM, Terhalle W, Dress AW., Mol. Biol. Evol. 17(1), 2000
PMID: 10666716
Covariation of residues in the homeodomain sequence family.
Clarke ND., Protein Sci. 4(11), 1995
PMID: 8563623

Covariation of mutations in the V3 loop of human immunodeficiency virus type 1 envelope protein: an information theoretic analysis.
Korber BT, Farber RM, Wolpert DH, Lapedes AS., Proc. Natl. Acad. Sci. U.S.A. 90(15), 1993
PMID: 8346232




The rapid generation of mutation data matrices from protein sequences.
Jones DT, Taylor WR, Thornton JM., Comput. Appl. Biosci. 8(3), 1992
PMID: 1633570
Exhaustive matching of the entire protein sequence database.
Gonnet GH, Cohen MA, Benner SA., Science 256(5062), 1992
PMID: 1604319
Amino acid substitution matrices from protein blocks.
Henikoff S, Henikoff JG., Proc. Natl. Acad. Sci. U.S.A. 89(22), 1992
PMID: 1438297
A novel use of equilibrium frequencies in models of sequence evolution.
Goldman N, Whelan S., Mol. Biol. Evol. 19(11), 2002
PMID: 12411592
An analysis of non-bonded energy of proteins.
Oobatake M, Ooi T., J. Theor. Biol. 67(3), 1977
PMID: 904331
Conformation of amino acid side-chains in proteins.
Janin J, Wodak S., J. Mol. Biol. 125(3), 1978
PMID: 731698



A natural classification of the basic helix-loop-helix class of transcription factors.
Atchley WR, Fitch WM., Proc. Natl. Acad. Sci. U.S.A. 94(10), 1997
PMID: 9144210
Phylogenetic analysis of the human basic helix-loop-helix proteins.
Ledent V, Paquet O, Vervoort M., Genome Biol. 3(6), 2002
PMID: 12093377

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