Publications
Found 23 results
Filters: Author is Y. Huang [Clear All Filters]
“Comparison and analysis of Wuding and avian chicken skeletal muscle satellite cells”, vol. 15, p. -, 2016.
, “Comparison and analysis of Wuding and avian chicken skeletal muscle satellite cells”, vol. 15, p. -, 2016.
, “Structure of mitochondrial DNA control region and genetic diversity of Moschus berezovskii populations in Shaanxi Province”, vol. 15, p. -, 2016.
, , , “Analysis of the relationship between peripheral blood T lymphocyte subsets and HCV RNA levels in patients with chronic hepatitis C”, vol. 14, pp. 10057-10063, 2015.
, “Cyclin D1 G870A polymorphism is associated with an increased risk of multiple myeloma”, vol. 14, pp. 5856-5861, 2015.
, “Dynamic changes of virus load in supernatant of primary CEK cell culture infected with different generations of avian infectious bronchitis virus strains Sczy3 as revealed by real-time reverse transcription-polymerase chain reaction”, vol. 14, pp. 6340-6349, 2015.
, “Evaluation of concentrations of botulinum toxin A for the treatment of hemifacial spasm: a randomized double-blind crossover trial”, vol. 14, pp. 1136-1144, 2015.
, “Genomic identification of group A bZIP transcription factors and their responses to abiotic stress in carrot”, vol. 14, pp. 13274-13288, 2015.
, “Positive association between PPARD rs2016520 polymorphism and coronary heart disease in a Han Chinese population”, vol. 14, pp. 6350-6359, 2015.
, “Role of autoantibodies to various Ro60 epitopes in the decrease of lymphocytes seen in systemic lupus erythematosus and primary Sjögren’s syndrome”, vol. 14, pp. 10096-10102, 2015.
, “Sequence characterization and phylogenetic analysis of toll-like receptor (TLR) 4 gene in the Tibetan macaque (Macaca thibetana)”, vol. 14, pp. 1875-1886, 2015.
, “Significant interaction of APOE rs4420638 polymorphism with HDL-C and APOA-I levels in coronary heart disease in Han Chinese men”, vol. 14, pp. 13414-13424, 2015.
, “Association of GSTTI and GSTM1 variants with acute myeloid leukemia risk”, vol. 13, pp. 3681-3685, 2014.
, “Discovery of somatic mutations in the progression of chronic myeloid leukemia by whole-exome sequencing”, vol. 13, pp. 945-953, 2014.
, “Critical evaluation of transcription factor Atf2 as a candidate modulator of alcohol preference in mouse and human populations”, vol. 12, pp. 5992-6005, 2013.
, “Genetic diversity among red swamp crayfish (Procambarus clarkii) populations in the middle and lower reaches of the Yangtze River based on AFLP markers”, vol. 12, pp. 791-800, 2013.
, Agrestia JJ, Agrestia JJ, Agrestia JJ, Poompuang S, et al. (2000). Breeding new strains of tilapia: development of an artificial center of origin and linkage map based on AFLP and microsatellite loci. Aquaculture 185: 43-56.
http://dx.doi.org/10.1016/S0044-8486(99)00335-X
Astanei I, Gosling E, Wilson J and Powell E (2005). Genetic variability and phylogeography of the invasive zebra mussel, Dreissena polymorpha (Pallas). Mol. Ecol. 14: 1655-1666.
http://dx.doi.org/10.1111/j.1365-294X.2005.02530.x
PMid:15836640
Austin CM and Knott B (1996). Systematics of the freswater crayfish Genus Cherax Erichson (Decapoda: Parastacidae) in south-western Australia: electrophoretic, morphological and habitat variation. Aust. J. Zool. 44: 223-258.
http://dx.doi.org/10.1071/ZO9960223
Barbaresi S and Gherardi F (2000). The invasion of the alien crayfish Procambarus clarkii in Europe, with particular reference to Italy. Biol. Inv. 2: 259-264.
http://dx.doi.org/10.1023/A:1010009701606
Barbaresi S, Fani R, Gherardi F, Mengoni A, et al. (2003). Genetic variability in European populations of an invasive American crayfish: preliminary results. Biol. Inv. 5: 269-274.
http://dx.doi.org/10.1023/A:1026133519707
Belfiore NM and May B (2003). Variable microsatellite loci in red swamp crayfish, Procambarus clarkii, and their characterization in other crayfish taxa. Mol. Ecol. 9: 2230-2234.
http://dx.doi.org/10.1046/j.1365-294X.2000.105339.x
Doyle RW, Perez-Enriquez R, Takagi M and Taniguchi N (2001). Selective recovery of founder genetic diversity in aquacultural broodstocks and captive, endangered fish populations. Genetica 111: 291-304.
http://dx.doi.org/10.1023/A:1013772205330
PMid:11841174
Excoffier L, Laval G and Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol. Bioinformatics Online 1: 47-50.
PMCid:2658868
Gherardi F, Renai B and Corti C (2001). Crayfish predation on tadpoles: a comparison between a native (Austropotamobius pallipes) and an alien species (Procambarus clarkii). Bull. Fr. Pêche Piscic. 361: 659-668.
http://dx.doi.org/10.1051/kmae:2001011
Gouin N, Grandjean F, Bouchon D, Reynolds JD, et al. (2001). Population genetic structure of the endangered freshwater crayfish Austropotamobius pallipes, assessed using RAPD markers. Heredity 87: 80-87.
http://dx.doi.org/10.1046/j.1365-2540.2001.00909.x
PMid:11678990
Guo JG, Vounatsou P, Cao CL, Utzinger J, et al. (2005). A geographic information and remote sensing based model for prediction of Oncomelania hupensis habitats in the Poyang Lake area, China. Acta Trop. 96: 213-222.
http://dx.doi.org/10.1016/j.actatropica.2005.07.029
PMid:16140246
Hedgecock D, Stelmach DJ, Nelson K, Lindenfelser ME, et al. (1979). Genetic divergence and biogeography of natural populations of Macrobrachium rosenbergii. Proc. World Maricul. Soc. 10: 873-879.
http://dx.doi.org/10.1111/j.1749-7345.1979.tb00084.x
Herborg LM, Weetman D, van Oosterhout C and Hanfling B (2007). Genetic population structure and contemporary dispersal patterns of a recent European invader, the Chinese mitten crab, Eriocheir sinensis. Mol. Ecol. 16: 231-242.
http://dx.doi.org/10.1111/j.1365-294X.2006.03133.x
PMid:17217341
Kolbe JJ, Glor RE, Rodriguez SL, Lara AC, et al. (2004). Genetic variation increases during biological invasion by a Cuban lizard. Nature 431: 177-181.
http://dx.doi.org/10.1038/nature02807
PMid:15356629
Lande R (2002). Mutation and conservation. Conserv. Biol. 9: 782-791.
http://dx.doi.org/10.1046/j.1523-1739.1995.09040782.x
Lindqvist OV and Huner JV (1999). Life History Characteristics of Crayfish: What Makes Some of Them Good Colonizers? In: Crayfish in Europe as Alien Species. How to Make the Best of a Bad Situation? (Gherardi F, ed.). A.A. Balkema, Rotterdam, 23-30.
Maheswaran M, Subudhi PK, Nandi S, Xu JC, et al. (1997). Polymorphism, distribution, and segregation of AFLP markers in a doubled haploid rice population. Theor. Appl. Genet. 94: 39-45.
http://dx.doi.org/10.1007/s001220050379
PMid:19352743
Mickett K, Morton C, Feng J, Li P, et al. (2003). Assessing genetic diversity of domestic populations of channel catfish (Ictalurus punctatus) in Alabama using AFLP markers. Aquaculture 228: 91-105.
http://dx.doi.org/10.1016/S0044-8486(03)00311-9
Nei M (1972). Genetic distance between populations. Am. Nat. 106: 283-292.
http://dx.doi.org/10.1086/282771
Nei M (1978). Estimation of average heterozyosity and genetic distance from a small number of individuals. Genetics 89: 583-590.
PMid:17248844 PMCid:1213855
Nei M (1988). Genetic Distance and Molecular Phylogeny. In: Population Genetics and Fishery Management (Ryman N and Utter FM, eds.) Washington Sea Grant Program, Distributed by University of Washington Press, Seattle and London, 193-223.
Oidtmann B, Schaefers N, Cerenius L, Soderhall K, et al. (2004). Detection of genomic DNA of the crayfish plague fungus Aphanomyces astaci (Oomycete) in clinical samples by PCR. Vet. Microbiol. 100: 269-282.
http://dx.doi.org/10.1016/j.vetmic.2004.01.019
PMid:15145505
Paglianti A and Gherardi F (2004). Combined effects of temperature and diet on growth and survival of YOY crayfish: a comparison between indigenous and invasive species. J. Crustacean Biol. 24: 140-148.
http://dx.doi.org/10.1651/C-2374
Powell W, Morgante M, Andre C, Hanafey M, et al. (1996). The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol. Breed. 2: 225-238.
http://dx.doi.org/10.1007/BF00564200
Reed DH and Frankham R (2003). Correlation between fitness and genetic diversity. Conserv. Biol. 17: 230-237.
http://dx.doi.org/10.1046/j.1523-1739.2003.01236.x
Renai B and Gherardi F (2004). Predatory efficiency of crayfish: comparison between indigenous and non-indigenous species. Biol. Inv. 6: 89-99.
http://dx.doi.org/10.1023/B:BINV.0000010126.94675.50
Rodríguez-Serna M, Carmona-Osalde C, Olvera-Novoa MA and Arredondo-Figuero JL (2000). Fecundity, egg development and growth of juvenile crayfish Procambarus (Austrocambarus) llamasi (Villalobos 1955) under laboratory conditions. Aquac. Res. 31: 173-179.
http://dx.doi.org/10.1046/j.1365-2109.2000.00409.x
Rodríguez CF, Bécares E, Fernández-Aláez M and Fernández-Aláez C (2005). Loss of diversity and degradation of wetlands as a result of introducing exotic crayfish. Biol. Inv. 7: 75-85.
http://dx.doi.org/10.1007/s10530-004-9636-7
Rozas J, Hernandez M, Cabrera VM and Prevosti A (1990). Colonization of America by Drosophila subobscura: effect of the founder event on the mitochondrial DNA polymorphism. Mol. Biol. Evol. 7: 103-109.
PMid:2299979
Skurdal J and Taugbøl T (1994). Do we need harvest regulations for European crayfish? Rev. Fish Biol. Fish. 4: 461-485.
http://dx.doi.org/10.1007/BF00042890
Song J, Song ZB, Yue BS and Zheng WJ (2006). Assessing genetic diversity of wild populations of Prenant's schizothoracin, Schizothorax prenanti, using AFLP Markers. Environm. Biol. Fish. 77: 79-86.
http://dx.doi.org/10.1007/s10641-006-9056-x
Spielman D, Brook BW and Frankham R (2004). Most species are not driven to extinction before genetic factors impact them. Proc. Nat. Acad. Sci. U. S. A. 101: 15261-15264.
http://dx.doi.org/10.1073/pnas.0403809101
PMid:15477597 PMCid:524053
Usio N and Townsend CR (2004). Roles of crayfish: consequences of predation and bioturbation for stream invertebrates. Ecology 85: 807-822.
http://dx.doi.org/10.1890/02-0618
Villanelli F and Gherardi F (1998). Breeding in the crayfish, Austropotamobius pallipes: mating patterns, mate choice and intermale competition. Freshwater Biol. 40: 305-315.
http://dx.doi.org/10.1046/j.1365-2427.1998.00355.x
Vos P, Hogers R, Bleeker M, Reijans M, et al. (1995). AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23: 4407-4414.
http://dx.doi.org/10.1093/nar/23.21.4407
PMid:7501463 PMCid:307397
Wang ZY, Tsoi KH and Chu KH (2004). Applications of AFLP technology in genetic and phylogenetic analysis of penaeid shrimp. Biochem. Syst. Ecol. 32: 399-407.
http://dx.doi.org/10.1016/j.bse.2003.10.006
Wilson AB, Naish KA and Boulding EG (1999). Multiple dispersal strategies of the invasive quagga mussel (Dreissena bugensis) as revealed by microsatellite analyses. Can. J. Fish. Aquat. Sci. 56: 2248-2261.
http://dx.doi.org/10.1139/f99-162
Yue GH, Li Y, Lim LC and Orban L (2004). Monitoring the genetic diversity of three Asian arowana (Scleropages formosus) captive stocks using AFLP and microsatellites. Aquaculture 237: 89-102.
http://dx.doi.org/10.1016/j.aquaculture.2004.04.003
Yue GH, Li J, Bai ZY, Wang CM, et al. (2010). Genetic diversity and population structure of the invasive alien red swamp crayfish. Biol. Inv. 12: 2697-2706.
http://dx.doi.org/10.1007/s10530-009-9675-1
“Potential role of Atp5g3 in epigenetic regulation of alcohol preference or obesity from a mouse genomic perspective”, vol. 12, pp. 3662-3674, 2013.
, “Benchmark comparison of ab initio microRNA identification methods and software”, vol. 11, pp. 4525-4538, 2012.
, Batuwita R and Palade V (2009). microPred: effective classification of pre-miRNAs for human miRNA gene prediction. Bioinformatics 25: 989-995.
http://dx.doi.org/10.1093/bioinformatics/btp107
PMid:19233894
Bentwich I, Avniel A, Karov Y, Aharonov R, et al. (2005). Identification of hundreds of conserved and nonconserved human microRNAs. Nat. Genet. 37: 766-770.
http://dx.doi.org/10.1038/ng1590
PMid:15965474
Borchert GM, Lanier W and Davidson BL (2006). RNA polymerase III transcribes human microRNAs. Nat. Struct. Mol. Biol. 13: 1097-1101.
http://dx.doi.org/10.1038/nsmb1167
PMid:17099701
Brennecke J, Hipfner DR, Stark A, Russell RB, et al. (2003). bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 113: 25-36.
http://dx.doi.org/10.1016/S0092-8674(03)00231-9
Carrington JC and Ambros V (2003). Role of microRNAs in plant and animal development. Science 301: 336-338.
http://dx.doi.org/10.1126/science.1085242
PMid:12869753
Friedlander MR, Chen W, Adamidi C, Maaskola J, et al. (2008). Discovering microRNAs from deep sequencing data using miRDeep. Nat. Biotechnol. 26: 407-415.
http://dx.doi.org/10.1038/nbt1394
PMid:18392026
Hackenberg M, Sturm M, Langenberger D, Falcon-Perez JM, et al. (2009). miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res. 37: W68-W76.
http://dx.doi.org/10.1093/nar/gkp347
PMid:19433510 PMCid:2703919
Hofacker IL (2003). Vienna RNA secondary structure server. Nucleic Acids Res. 31: 3429-3431.
http://dx.doi.org/10.1093/nar/gkg599
PMid:12824340 PMCid:169005
Huang JC, Babak T, Corson TW, Chua G, et al. (2007). Using expression profiling data to identify human microRNA targets. Nat. Methods 4: 1045-1049.
http://dx.doi.org/10.1038/nmeth1130
PMid:18026111
Huang Y, Zou Q, Tang SM, Wang LG, et al. (2010). Computational identification and characteristics of novel microRNAs from the silkworm (Bombyx mori L.). Mol. Biol. Rep. 37: 3171-3176.
http://dx.doi.org/10.1007/s11033-009-9897-4
PMid:19823945
Huang Y, Shen XJ, Zou Q, Wang SP, et al. (2011a). Biological functions of microRNAs: a review. J. Physiol. Biochem. 67: 129-139.
http://dx.doi.org/10.1007/s13105-010-0050-6
PMid:20981514
Huang Y, Zou Q, Wang SP, Tang SM, et al. (2011b). The discovery approaches and detection methods of microRNAs. Mol. Biol. Rep. 38: 4125-4135.
http://dx.doi.org/10.1007/s11033-010-0532-1
PMid:21107708
Jiang P, Wu H, Wang W, Ma W, et al. (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res. 35: W339-W344.
http://dx.doi.org/10.1093/nar/gkm368
PMid:17553836 PMCid:1933124
Kumar S, Ansari FA and Scaria V (2009). Prediction of viral microRNA precursors based on human microRNA precursor sequence and structural features. Virol. J. 6: 129.
http://dx.doi.org/10.1186/1743-422X-6-129
PMid:19691855 PMCid:2743665
Lee Y, Ahn C, Han J, Choi H, et al. (2003). The nuclear RNase III Drosha initiates microRNA processing. Nature 425: 415-419.
http://dx.doi.org/10.1038/nature01957
PMid:14508493
Li PW, Lu XY, Li CZ, Fang J, et al. (2007). Advances in the study of plant microRNAs. Yi Chuan 29: 283-288.
http://dx.doi.org/10.1360/yc-007-0283
PMid:17369147
Lim LP, Lau NC, Weinstein EG, Abdelhakim A, et al. (2003). The microRNAs of Caenorhabditis elegans. Genes Dev.
http://dx.doi.org/10.1101/gad.1074403
Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, et al. (2000). The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403: 901-906.
http://dx.doi.org/10.1038/35002607
PMid:10706289
Ruby JG, Jan C, Player C, Axtell MJ, et al. (2006). Large-scale sequencing reveals 21U-RNAs and additional microRNAs and endogenous siRNAs in C. elegans. Cell 127: 1193-1207.
http://dx.doi.org/10.1016/j.cell.2006.10.040
PMid:17174894
Sankoff D, Kruskal JB, Mainville S and Cedergren RJ (1983). Fast Algorithms to Determine RNA Secondary Structures Containing Multiple Loops. In: Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison (Sankoff D and Kruskal JB, eds.). Chapter 3. Addison-Wesley, Reading, 93-120.
Sewer A, Paul N, Landgraf P, Aravin A, et al. (2005). Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 6: 267.
http://dx.doi.org/10.1186/1471-2105-6-267
PMid:16274478 PMCid:1315341
Wang X, Zhang J, Li F, Gu J, et al. (2005). MicroRNA identification based on sequence and structure alignment. Bioinformatics 21: 3610-3614.
http://dx.doi.org/10.1093/bioinformatics/bti562
PMid:15994192
Wu Y, Wei B, Liu H, Li T, et al. (2011). MiRPara: a SVM-based software tool for prediction of most probable microRNA
Genetics and Molecular Research 11 (4): 4525-4538 (2012) ©FUNPEC-RP www.funpecrp.com.br
L.L. Hu et al. 4538 coding regions in genome scale sequences. BMC Bioinformatics 12: 107.
Xue C, Li F, He T, Liu GP, et al. (2005). Classification of real and pseudo microRNA precursors using local structuresequence features and support vector machine. BMC Bioinformatics 6: 310.
http://dx.doi.org/10.1186/1471-2105-6-310
PMid:16381612 PMCid:1360673
Yousef M, Nebozhyn M, Shatkay H, Kanterakis S, et al. (2006). Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier. Bioinformatics 22: 1325-1334.
http://dx.doi.org/10.1093/bioinformatics/btl094
PMid:16543277
Zeng Y, Yi R and Cullen BR (2005). Recognition and cleavage of primary microRNA precursors by the nuclear processing enzyme Drosha. EMBO J. 24: 138-148.
http://dx.doi.org/10.1038/sj.emboj.7600491
PMid:15565168 PMCid:544904
Zou Q, Zhao T, Liu Y and Guo M (2009). Predicting RNA secondary structure based on the class information and Hopfield network. Comput. Biol. Med. 39: 206-214.
http://dx.doi.org/10.1016/j.compbiomed.2008.12.010
PMid:19215914
Zou Q, Lin C, Liu XY, Han YP, et al. (2011). Novel representation of RNA secondary structure used to improve prediction algorithms. Genet. Mol. Res. 10: 1986-1998.
http://dx.doi.org/10.4238/vol10-3gmr1181
PMid:21948761
Zuker M (1989a). Computer prediction of RNA structure. Methods Enzymol. 180: 262-288.
http://dx.doi.org/10.1016/0076-6879(89)80106-5
Zuker M (1989b). On finding all suboptimal foldings of an RNA molecule. Science 244: 48-52.
http://dx.doi.org/10.1126/science.2468181
PMid:2468181
Zuker M (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31: 3406-3415.
http://dx.doi.org/10.1093/nar/gkg595
PMid:12824337 PMCid:169194
Zuker M and Stiegler P (1981). Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res. 9: 133-148.
http://dx.doi.org/10.1093/nar/9.1.133
PMid:6163133 PMCid:326673
“Improved method for predicting protein fold patterns with ensemble classifiers”, vol. 11, pp. 174-181, 2012.
, Boisvert S, Marchand M, Laviolette F and Corbeil J (2008). HIV-1 coreceptor usage prediction without multiple alignments: an application of string kernels. Retrovirology 5: 110.
http://dx.doi.org/10.1186/1742-4690-5-110
PMid:19055831 PMCid:2637298
Breimin L (2001). Random forests. Machine Learn. 45: 5-32.
http://dx.doi.org/10.1023/A:1010933404324
Cai CZ, Han LY, Ji ZL, Chen X, et al. (2003). SVM-Prot: Web-based support vector machine software for functional classification of a protein from its primary sequence. Nucleic Acids Res. 31: 3692-3697.
http://dx.doi.org/10.1093/nar/gkg600
PMid:12824396 PMCid:169006
Call ME, Schnell JR, Xu C, Lutz RA, et al. (2006). The structure of the zetazeta transmembrane dimer reveals features essential for its assembly with the T cell receptor. Cell 127: 355-368.
http://dx.doi.org/10.1016/j.cell.2006.08.044
PMid:17055436
Chen K and Kurgan L (2007). PFRES: protein fold classification by using evolutionary information and predicted secondary structure. Bioinformatics 23: 2843-2850.
http://dx.doi.org/10.1093/bioinformatics/btm475
PMid:17942446
Chou KC (2004). Structural bioinformatics and its impact to biomedical science. Curr. Med. Chem. 11: 2105-2134.
PMid:15279552
Ding CHQ and Dubchak I (2001). Multi-class protein fold recognition using support vector machines and neural networks. Bioinformatics 17: 349-358.
http://dx.doi.org/10.1093/bioinformatics/17.4.349
PMid:11301304
Douglas SM, Chou JJ and Shih WM (2007). DNA-nanotube-induced alignment of membrane proteins for NMR structure determination. Proc. Natl. Acad. Sci. U. S. A. 104: 6644-6648.
http://dx.doi.org/10.1073/pnas.0700930104
PMid:17404217 PMCid:1871839
Gao WN, Wei DQ, Li Y, Gao H, et al. (2007). Agaritine and its derivatives are potential inhibitors against HIV proteases. Med. Chem. 3: 221-226.
http://dx.doi.org/10.2174/157340607780620644
PMid:17504192
Honda M, Kawai H, Shirota Y, Yamashita T, et al. (2005). cDNA microarray analysis of autoimmune hepatitis, primary biliary cirrhosis and consecutive disease manifestation. J. Autoimmun. 25: 133-140.
http://dx.doi.org/10.1016/j.jaut.2005.03.009
PMid:16150573
Li Y, Wei DQ, Gao WN, Gao H, et al. (2007). Computational approach to drug design for oxazolidinones as antibacterial agents. Med. Chem. 3: 576-582.
http://dx.doi.org/10.2174/157340607782360362
PMid:18045208
Murzin AG, Brenner SE, Hubbard T and Chothia C (1995). SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247: 536-540.
http://dx.doi.org/10.1016/S0022-2836(05)80134-2
Nanni L (2006). A novel ensemble of classifiers for protein fold recognition. Neurocomputing 69: 2434-2437.
http://dx.doi.org/10.1016/j.neucom.2006.01.026
Niels L, Mark H and Eibe F (2005). Logistic model trees. Machine Learn 95: 161-205.
Pu X, Guo J, Leung H and Lin Y (2007). Prediction of membrane protein types from sequences and position-specific scoring matrices. J. Theor. Biol. 247: 259-265.
http://dx.doi.org/10.1016/j.jtbi.2007.01.016
PMid:17433369
Schaffer AA, Aravind L, Madden TL, Shavirin S, et al. (2001). Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements. Nucleic Acids Res. 29: 2994-3005.
http://dx.doi.org/10.1093/nar/29.14.2994
PMid:11452024 PMCid:55814
Schnell JR and Chou JJ (2008). Structure and mechanism of the M2 proton channel of influenza A virus. Nature 451: 591-595.
http://dx.doi.org/10.1038/nature06531
PMid:18235503 PMCid:3108054
Shen HB and Chou KC (2006). Ensemble classifier for protein fold pattern recognition. Bioinformatics 22: 1717-1722.
http://dx.doi.org/10.1093/bioinformatics/btl170
PMid:16672258
Shen HB and Chou KC (2009). Predicting protein fold pattern with functional domain and sequential evolution information. J. Theor. Biol. 256: 441-446.
http://dx.doi.org/10.1016/j.jtbi.2008.10.007
PMid:18996396
Sumner M, Frank E and Hall MA (2005). Speeding up Logistic Model Tree Induction. In: Proceedings of 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal (Jorge A, ed.). Springer, Germany, 675-683.
Vendruscolo M and Dobson CM (2005). A glimpse at the organization of the protein universe. PNAS 102: 5641-5642.
http://dx.doi.org/10.1073/pnas.0500274102
PMid:15827120 PMCid:556289
“Patterns of synonymous codon usage bias in the model grass Brachypodium distachyon”, vol. 11, pp. 4695-4706, 2012.
, Bulmer M (1988). Are codon usage patterns in unicellular organisms determined by selection-mutation balance? J. Mol. Biol. 1: 15-26.
Bulmer M (1991). The selection-mutation-drift theory of synonymous codon usage. Genetics 129: 897-907.
PMid:1752426 PMCid:1204756
Carels N and Bernardi G (2000). Two classes of genes in plants. Genetics 154: 1819-1825.
PMid:10747072 PMCid:1461008
Chiapello H, Lisacek F, Caboche M and Henaut A (1998). Codon usage and gene function are related in sequences of Arabidopsis thaliana. Gene 209: GC1-GC38.
http://dx.doi.org/10.1016/S0378-1119(97)00671-9
De Amicis F and Marchetti S (2000). Intercodon dinucleotides affect codon choice in plant genes. Nucleic Acids Res. 28: 3339-3345.
http://dx.doi.org/10.1093/nar/28.17.3339
PMid:10954603 PMCid:110687
Doust A (2007). Architectural evolution and its implications for domestication in grasses. Ann. Bot. 100: 941-950.
http://dx.doi.org/10.1093/aob/mcm040
PMid:17478546 PMCid:2759198
Draper J, Mur LA, Jenkins G, Ghosh-Biswas GC, et al. (2001). Brachypodium distachyon. A new model system for functional genomics in grasses. Plant Physiol. 127: 1539-1555.
http://dx.doi.org/10.1104/pp.010196
PMid:11743099 PMCid:133562
Duret L and Mouchiroud D (1999). Expression pattern and, surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis. Proc. Natl. Acad. Sci. U. S. A. 96: 4482-4487.
http://dx.doi.org/10.1073/pnas.96.8.4482
PMid:10200288 PMCid:16358
Eyre-Walker AC (1991). An analysis of codon usage in mammals: selection or mutation bias? J. Mol. Evol. 33: 442-449.
http://dx.doi.org/10.1007/BF02103136
PMid:1960741
Gupta SK, Bhattacharyya TK and Ghosh TC (2004). Synonymous codon usage in Lactococcus lactis: mutational bias versus translational selection. J. Biomol. Struct. Dyn. 21: 527-536.
http://dx.doi.org/10.1080/07391102.2004.10506946
PMid:14692797
Hershberg R and Petrov DA (2008). Selection on codon bias. Annu. Rev. Genet. 42: 287-299.
http://dx.doi.org/10.1146/annurev.genet.42.110807.091442
PMid:18983258
International Brachypodium Initiative (2010). Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature 463: 763-768.
http://dx.doi.org/10.1038/nature08747
PMid:20148030
Jiang Y, Deng F, Wang H and Hu Z (2008). An extensive analysis on the global codon usage pattern of baculoviruses. Arch. Virol. 153: 2273-2282.
http://dx.doi.org/10.1007/s00705-008-0260-1
PMid:19030954
Kawabe A and Miyashita NT (2003). Patterns of codon usage bias in three dicot and four monocot plant species. Genes Genet. Syst. 78: 343-352.
http://dx.doi.org/10.1266/ggs.78.343
PMid:14676425
Liu H, He R, Zhang H, Huang Y, et al. (2010). Analysis of synonymous codon usage in Zea mays. Mol. Biol. Rep. 37: 677-684.
http://dx.doi.org/10.1007/s11033-009-9521-7
PMid:19330534
Liu Q (2006). Analysis of codon usage pattern in the radioresistant bacterium Deinococcus radiodurans. Biosystems 85: 99-106.
http://dx.doi.org/10.1016/j.biosystems.2005.12.003
PMid:16431014
Liu Q and Xue Q (2005). Comparative studies on codon usage pattern of chloroplasts and their host nuclear genes in four plant species. J. Genet. 84: 55-62.
http://dx.doi.org/10.1007/BF02715890
PMid:15876584
Liu Q, Feng Y, Zhao X, Dong H, et al. (2004). Synonymous codon usage bias in Oryza sativa. Plant Sci. 167: 101-105.
http://dx.doi.org/10.1016/j.plantsci.2004.03.003
Liu Q, Dou S, Ji Z and Xue Q (2005). Synonymous codon usage and gene function are strongly related in Oryza sativa. Biosystems 80: 123-131.
http://dx.doi.org/10.1016/j.biosystems.2004.10.008
PMid:15823411
Mitreva M, Wendl MC, Martin J, Wylie T, et al. (2006). Codon usage patterns in Nematoda: analysis based on over 25 million codons in thirty-two species. Genome Biol. 7: R75.
http://dx.doi.org/10.1186/gb-2006-7-8-r75
PMCid:1779591
Morton BR and Wright SI (2007). Selective constraints on codon usage of nuclear genes from Arabidopsis thaliana. Mol. Biol. Evol. 24: 122-129.
http://dx.doi.org/10.1093/molbev/msl139
PMid:17021276
Mukhopadhyay P, Basak S and Ghosh TC (2007a). Synonymous codon usage in different protein secondary structural classes of human genes: implication for increased non-randomness of GC3 rich genes towards protein stability. J. Biosci. 32: 947-963.
http://dx.doi.org/10.1007/s12038-007-0095-z
PMid:17914237
Mukhopadhyay P, Basak S and Ghosh TC (2007b). Nature of selective constraints on synonymous codon usage of rice differs in GC-poor and GC-rich genes. Gene 400: 71-81.
http://dx.doi.org/10.1016/j.gene.2007.05.027
PMid:17629420
Murray EE, Lotzer J and Eberle M (1989). Codon usage in plant genes. Nucleic Acids Res. 17: 477-498.
http://dx.doi.org/10.1093/nar/17.2.477
PMid:2644621 PMCid:331598
Naya H, Romero H, Carels N, Zavala A, et al. (2001). Translational selection shapes codon usage in the GC-rich genome of Chlamydomonas reinhardtii. FEBS Lett. 501: 127-130.
http://dx.doi.org/10.1016/S0014-5793(01)02644-8
Peraldi A, Beccari G, Steed A and Nicholson P (2011). Brachypodium distachyon: a new pathosystem to study Fusarium head blight and other Fusarium diseases of wheat. BMC Plant Biol. 11: 100.
http://dx.doi.org/10.1186/1471-2229-11-100
PMid:21639892 PMCid:3123626
Roychoudhury S and Mukherjee D (2010). A detailed comparative analysis on the overall codon usage pattern in herpesviruses. Virus Res. 148: 31-43.
http://dx.doi.org/10.1016/j.virusres.2009.11.018
PMid:19969032
Sharp PM and Li WH (1987). The codon Adaptation Index - a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res. 15: 1281-1295.
http://dx.doi.org/10.1093/nar/15.3.1281
PMid:3547335 PMCid:340524
Sharp PM, Stenico M, Peden JF and Lloyd AT (1993). Codon usage: mutational bias, translational selection, or both? Biochem. Soc. Trans. 21: 835-841.
PMid:8132077
Shields DC and Sharp PM (1987). Synonymous codon usage in Bacillus subtilis reflects both translational selection and mutational biases. Nucleic Acids Res. 15: 8023-8040.
http://dx.doi.org/10.1093/nar/15.19.8023
PMid:3118331 PMCid:306324
Shields DC, Sharp PM, Higgins DG and Wright F (1988). "Silent" sites in Drosophila genes are not neutral: evidence of selection among synonymous codons. Mol. Biol. Evol. 5: 704-716.
PMid:3146682
Stenico M, Lloyd AT and Sharp PM (1994). Codon usage in Caenorhabditis elegans: delineation of translational selection and mutational biases. Nucleic Acids Res. 22: 2437-2446.
http://dx.doi.org/10.1093/nar/22.13.2437
PMid:8041603 PMCid:308193
Sueoka N (1988). Directional mutation pressure and neutral molecular evolution. Proc. Natl. Acad. Sci. U. S. A. 85: 2653-2657.
http://dx.doi.org/10.1073/pnas.85.8.2653
PMid:3357886 PMCid:280056
Sueoka N and Kawanishi Y (2000). DNA G+C content of the third codon position and codon usage biases of human genes. Gene 261: 53-62.
http://dx.doi.org/10.1016/S0378-1119(00)00480-7
Wang HC and Hickey DA (2007). Rapid divergence of codon usage patterns within the rice genome. BMC Evol. Biol. 7: S6.
http://dx.doi.org/10.1186/1471-2148-7-S1-S6
PMid:17288579 PMCid:1796615
Wright F (1990). The 'effective number of codons' used in a gene. Gene 87: 23-29.
http://dx.doi.org/10.1016/0378-1119(90)90491-9
Zhang WJ, Zhou J, Li ZF, Wang L, et al. (2007). Comparative analysis of codon usage patterns among mitochondrion, chloroplast and nuclear genes in Triticum aestivum L. J. Integr. Plant Biol. 49: 246-254.
http://dx.doi.org/10.1111/j.1744-7909.2007.00404.x
Zhao S, Zhang Q, Chen Z, Zhao Y, et al. (2007). The factors shaping synonymous codon usage in the genome of Burkholderia mallei. J. Genet. Genomics 34: 362-372.
http://dx.doi.org/10.1016/S1673-8527(07)60039-3
“Single nucleotide polymorphisms in the ORM1-like 3 gene associated with childhood asthma in a Chinese population”, vol. 11, pp. 4646-4653, 2012.
, Adinoff AD, Rosloniec DM, McCall LL and Nelson HS (1990). Immediate skin test reactivity to Food and Drug Administration-approved standardized extracts. J. Allergy Clin. Immunol. 86: 766-774.
http://dx.doi.org/10.1016/S0091-6749(05)80181-2
Barton SJ, Koppelman GH, Vonk JM, Browning CA, et al. (2009). PLAUR polymorphisms are associated with asthma, PLAUR levels, and lung function decline. J. Allergy Clin. Immunol. 123: 1391-1400.
http://dx.doi.org/10.1016/j.jaci.2009.03.014
PMid:19443020
Bateman ED, Hurd SS, Barnes PJ, Bousquet J, et al. (2008). Global strategy for asthma management and prevention: GINA executive summary. Eur. Respir. J. 31: 143-178.
http://dx.doi.org/10.1183/09031936.00138707
PMid:18166595
Breslow DK, Collins SR, Bodenmiller B, Aebersold R, et al. (2010). Orm family proteins mediate sphingolipid homeostasis. Nature 463: 1048-1053.
http://dx.doi.org/10.1038/nature08787
PMid:20182505 PMCid:2877384
Cantero-Recasens G, Fandos C, Rubio-Moscardo F, Valverde MA, et al. (2010). The asthma-associated ORMDL3 gene product regulates endoplasmic reticulum-mediated calcium signaling and cellular stress. Hum. Mol. Genet. 19: 111-121.
http://dx.doi.org/10.1093/hmg/ddp471
PMid:19819884
Chen YZ (2003). A nationwide survey in China on prevalence of asthma in urban children. Zhonghua Er Ke Za Zhi 41: 123-127.
PMid:14759318
Chen YZ (2004). Recent status of prevention and treatment of asthma in children in China. Zhonghua Er Ke Za Zhi 42: 81-82.
PMid:15059477
Galanter J, Choudhry S, Eng C, Nazario S, et al. (2008). ORMDL3 gene is associated with asthma in three ethnically diverse populations. Am. J. Respir. Crit. Care Med. 177: 1194-1200.
http://dx.doi.org/10.1164/rccm.200711-1644OC
PMid:18310477 PMCid:2408437
Galanter JM, Choudhry S, Eng C, Nazario S, et al. (2009). Polymorphisms in the ORMDL3 gene are associated with earlyonsetaAsthma in African Americans. Am. J. Respir. Crit. Care Med. 179: A2743.
Halapi E, Gudbjartsson DF, Jonsdottir GM, Bjornsdottir US, et al. (2010). A sequence variant on 17q21 is associated with age at onset and severity of asthma. Eur. J. Hum. Genet. 18: 902-908.
http://dx.doi.org/10.1038/ejhg.2010.38
PMid:20372189 PMCid:2987388
Hirota T, Harada M, Sakashita M, Doi S, et al. (2008). Genetic polymorphism regulating ORM1-like 3 (Saccharomyces cerevisiae) expression is associated with childhood atopic asthma in a Japanese population. J. Allergy Clin. Immunol. 121: 769-770.
http://dx.doi.org/10.1016/j.jaci.2007.09.038
PMid:18155279
Hjelmqvist L, Tuson M, Marfany G, Herrero E, et al. (2002). ORMDL proteins are a conserved new family of endoplasmic reticulum membrane proteins. Genome Biol. 3: RESEARCH0027.
Hoffjan S and Ober C (2002). Present status on the genetic studies of asthma. Curr. Opin. Immunol. 14: 709-717.
http://dx.doi.org/10.1016/S0952-7915(02)00393-X
Koppelman GH (2006). Gene by environment interaction in asthma. Curr. Allergy Asthma Rep. 6: 103-111.
http://dx.doi.org/10.1007/s11882-006-0047-y
PMid:16566859
Leung TF, Sy HY, Ng MC, Chan IH, et al. (2009). Asthma and atopy are associated with chromosome 17q21 markers in Chinese children. Allergy 64: 621-628.
http://dx.doi.org/10.1111/j.1398-9995.2008.01873.x
PMid:19175592
Moffatt MF, Kabesch M, Liang L, Dixon AL, et al. (2007). Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature 448: 470-473.
http://dx.doi.org/10.1038/nature06014
PMid:17611496
Ober C and Hoffjan S (2006). Asthma genetics 2006: the long and winding road to gene discovery. Genes Immun. 7:
http://dx.doi.org/10.1038/sj.gene.6364284