Weiss FU, Laemmerhirt F, Lerch MM. Etiology and risk factors of acute and chronic pancreatitis. Visc Med. 2019;35:73–81. https://doi.org/10.1159/000499138.
Article
PubMed
PubMed Central
Google Scholar
Joergensen MT, Geisz A, Brusgaard K, Schaffalitzky de Muckadell OB, Hegyi P, Gerdes A-M, Sahin-Tóth M. Intragenic duplication: a novel mutational mechanism in hereditary pancreatitis. Pancreas. 2011;40:540–6. https://doi.org/10.1097/MPA.0b013e3182152fdf.
Article
PubMed
PubMed Central
Google Scholar
Geisz A, Hegyi P, Sahin-Tóth M. Robust autoactivation, chymotrypsin C independence and diminished secretion define a subset of hereditary pancreatitis-associated cationic trypsinogen mutants. FEBS J. 2013;280:2888–99. https://doi.org/10.1111/febs.12292.
Article
CAS
PubMed
PubMed Central
Google Scholar
LaRusch J, Whitcomb DC. Genetics of pancreatitis. Curr Opin Gastroenterol. 2011;27:467–74. https://doi.org/10.1097/MOG.0b013e328349e2f8.
Article
PubMed
PubMed Central
Google Scholar
Aoun E, Chang C-CH, Greer JB, Papachristou GI, Barmada MM, Whitcomb DC. Pathways to Injury in chronic pancreatitis: decoding the role of the high-risk SPINK1 N34S haplotype using meta-analysis. PLoS ONE. 2008;3: e2003. https://doi.org/10.1371/journal.pone.0002003.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ravi Kanth V, Nageshwar Reddy D. Genetics of acute and chronic pancreatitis: an update. World J Gastrointest Pathophysiol. 2014;5(4):427–37.
Article
PubMed
PubMed Central
Google Scholar
Masson E, Chen J-M, Audrézet M-P, Cooper DN, Férec C. A conservative assessment of the major genetic causes of idiopathic chronic pancreatitis: data from a comprehensive analysis of PRSS1, SPINK1, CTRC and CFTR genes in 253 young French patients. PLoS ONE. 2013;8: e73522. https://doi.org/10.1371/journal.pone.0073522.
Article
CAS
PubMed
PubMed Central
Google Scholar
Camiolo S, Farina L, Porceddu A. The relation of codon bias to tissue-specific gene expression in Arabidopsis thaliana. Genetics. 2012;192:641–9. https://doi.org/10.1534/genetics.112.143677.
Article
CAS
PubMed
PubMed Central
Google Scholar
Payne BL, Alvarez-Ponce D. Codon usage differences among genes expressed in different tissues of drosophila melanogaster. Genome Biol Evol. 2019;11:1054–65. https://doi.org/10.1093/gbe/evz051.
Article
CAS
PubMed
PubMed Central
Google Scholar
Deka H, Chakraborty S. Compositional constraint is the key force in shaping codon usage bias in hemagglutinin Gene in H1N1 subtype of influenza a Virus. Int J Genomics. 2014;2014: 349139. https://doi.org/10.1155/2014/349139.
Article
CAS
PubMed
PubMed Central
Google Scholar
Whittle CA, Extavour CG. Expression-linked patterns of codon usage amino acid frequency, and protein length in the basally branching arthropod parasteatoda tepidariorum. Genome Biol Evol. 2016;8(2722):2736.
Google Scholar
Khandia R, Alqahtani T, Alqahtani AM. Genes common in primary immunodeficiencies and cancer display overrepresentation of codon ctg and dominant role of selection pressure in shaping codon usage. Biomedicines. 2021;9:1001. https://doi.org/10.3390/biomedicines9081001.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ikemura T. Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli translational system. J Mol Biol. 1981;151(3):389–409.
Article
CAS
PubMed
Google Scholar
Lyu X, Yang Q, Zhao F, Liu Y. Codon usage and protein length-dependent feedback from translation elongation regulates translation initiation and elongation speed. Nucleic Acids Res. 2021;49:9404–23. https://doi.org/10.1093/nar/gkab729.
Article
CAS
PubMed
PubMed Central
Google Scholar
Sau K, Deb A. Temperature influences synonymous codon and amino acid usage biases in the phages infecting extremely thermophilic prokaryotes. In Silico Biol. 2009;9:1–9.
Article
CAS
PubMed
Google Scholar
Oresic M, Shalloway D. Specific correlations between relative synonymous codon usage and protein secondary structure. J Mol Biol. 1998;281:31–48. https://doi.org/10.1006/jmbi.1998.1921.
Article
CAS
PubMed
Google Scholar
Khandia R, Singhal S, Kumar U, Ansari A, Tiwari R, Dhama K, Das J, Munjal A, Singh RK. Analysis of nipah virus codon usage and adaptation to hosts. Front Microbiol. 2019;10:886. https://doi.org/10.3389/fmicb.2019.00886.
Article
PubMed
PubMed Central
Google Scholar
N.C. Edwards, Z.A. Hing, A. Perry, A. Blaisdell, D.B. Kopelman, R. Fathke, W. Plum, J. Newell, C.E. Allen, G. S, A. Shapiro, C. Okunji, I. Kosti, N. Shomron, V. Grigoryan, T.M. Przytycka, Z.E. Sauna, R. Salari, Y. Mandel-Gutfreund, A.A. Komar, C. Kimchi-Sarfaty, Characterization of coding synonymous and non-synonymous variants in ADAMTS13 using ex vivo and in silico approaches, PLoS One. 7 (2012) e38864. https://doi.org/10.1371/journal.pone.0038864.
Shomron N, Hamasaki-Katagiri N, Hunt R, Hershko K, Pommier E, Geetha S, Blaisdell A, Dobkin A, Marple A, Roma I, Newell J, Allen C, Friedman S, Kimchi-Sarfaty C. A splice variant of ADAMTS13 is expressed in human hepatic stellate cells and cancerous tissues. Thromb Haemost. 2010;104:531–5. https://doi.org/10.1160/TH09-12-0860.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zeng Z, Bromberg Y. Predicting functional effects of synonymous variants: a systematic review and perspectives. Front Genet. 2019;10:914. https://doi.org/10.3389/fgene.2019.00914.
Article
CAS
PubMed
PubMed Central
Google Scholar
Tang M, Alaniz ME, Felsky D, Vardarajan B, Reyes-Dumeyer D, Lantigua R, Medrano M, Bennett DA, de Jager PL, Mayeux R, Santa-Maria I, Reitz C. Synonymous variants associated with Alzheimer disease in multiplex families. Neurol Genet. 2020;6: e450. https://doi.org/10.1212/NXG.0000000000000450.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhou Z, Dang Y, Zhou M, Li L, Yu C-H, Fu J, Chen S, Liu Y. Codon usage is an important determinant of gene expression levels largely through its effects on transcription. Proc Natl Acad Sci U S A. 2016;113:E6117–25. https://doi.org/10.1073/pnas.1606724113.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mazumder TH, Alqahtani AM, Alqahtani T, Emran TB, Aldahish AA, Uddin A. Analysis of codon usage of speech gene FoxP2 among animals. Biology (Basel). 2021;10:1078. https://doi.org/10.3390/biology10111078.
Article
CAS
PubMed
Google Scholar
Zhang J, Wang M, Liu W, Zhou J, Chen H, Ma L, Ding Y, Gu Y, Liu Y. Analysis of codon usage and nucleotide composition bias in polioviruses. Virol J. 2011;8:146. https://doi.org/10.1186/1743-422X-8-146.
Article
CAS
PubMed
PubMed Central
Google Scholar
Charneski CA, Honti F, Bryant JM, Hurst LD, Feil EJ. Atypical at skew in Firmicute genomes results from selection and not from mutation. PLoS Genet. 2011;7: e1002283. https://doi.org/10.1371/journal.pgen.1002283.
Article
CAS
PubMed
PubMed Central
Google Scholar
Kolmogorov–Smirnov Test, in: The Concise Encyclopedia of Statistics, Springer, New York, NY, 2008: pp. 283–287. https://doi.org/10.1007/978-0-387-32833-1_214.
Berkhout B, Grigoriev A, Bakker M, Lukashov VV. Codon and amino acid usage in retroviral genomes is consistent with virus-specific nucleotide pressure. AIDS Res Hum Retroviruses. 2002;18:133–41. https://doi.org/10.1089/08892220252779674.
Article
CAS
PubMed
Google Scholar
S. Hassan, V. Mahalingam, V. Kumar, Synonymous codon usage analysis of thirty two mycobacteriophage genomes, Adv Bioinformatics. (2009) 316936. https://doi.org/10.1155/2009/316936.
Kumar U, Khandia R, Singhal S, Puranik N, Tripathi M, Pateriya AK, Khan R, Emran TB, Dhama K, Munjal A, Alqahtani T, Alqahtani AM. Insight into codon utilization pattern of tumor suppressor gene EPB41L3 from different mammalian species indicates dominant role of selection force. Cancers (Basel). 2021;13:2739. https://doi.org/10.3390/cancers13112739.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jenkins GM, Holmes EC. The extent of codon usage bias in human RNA viruses and its evolutionary origin. Virus Res. 2003;92:1–7. https://doi.org/10.1016/s0168-1702(02)00309-x.
Article
CAS
PubMed
Google Scholar
Majeed A, Kaur H, Bhardwaj P. Selection constraints determine preference for A/U-ending codons in Taxus contorta. Genome. 2020;63:215–24. https://doi.org/10.1139/gen-2019-0165.
Article
CAS
PubMed
Google Scholar
MA Ruzman AM Ripen H Mirsafian NFW Ridzwan AF Merican SB Mohamad 2021 Analysis of synonymous codon usage bias in human monocytes B, and T lymphocytes based on transcriptome data, Gene Reports 23 10103410.1016/j.genrep.2021.101034
M.N. Choudhury, A. Uddin, S. Chakraborty, Nucleotide composition and codon usage bias of SRY gene, Andrologia. 50 (2018). https://doi.org/10.1111/and.12787.
Long H, Sung W, Kucukyildirim S, Williams E, Miller SF, Guo W, Patterson C, Gregory C, Strauss C, Stone C, Berne C, Kysela D, Shoemaker WR, Muscarella ME, Luo H, Lennon JT, Brun YV, Lynch M. Evolutionary determinants of genome-wide nucleotide composition. Nat Ecol Evol. 2018;2:237–40. https://doi.org/10.1038/s41559-017-0425-y.
Article
PubMed
PubMed Central
Google Scholar
Gao NL, He Z, Zhu Q, Jiang P, Hu S, Chen W-H. Selection for cheaper amino acids drives nucleotide usage at the start of translation in eukaryotic genes. Genomics Proteomics Bioinformatics. 2021;S1672–0229(21):00060–7. https://doi.org/10.1016/j.gpb.2021.03.002.
Article
Google Scholar
Koski LB, Morton RA, Golding GB. Codon bias and base composition are poor indicators of horizontally transferred genes. Mol Biol Evol. 2001;18:404–12. https://doi.org/10.1093/oxfordjournals.molbev.a003816.
Article
CAS
PubMed
Google Scholar
Sahebi R, Ghazizadeh H, Avan A, Tayefi M, Saffar-Soflaei S, Mouhebati M, Esmaily H, Ferns GA, Hashemzadeh-Chaleshtori M, Ghayour-Mobarhan M, Farrokhi E. Association between a genetic variant in scavenger receptor class B type 1 and its role on codon usage bias with increased risk of developing coronary artery disease. Clin Biochem. 2021;95:60–5. https://doi.org/10.1016/j.clinbiochem.2021.06.001.
Article
CAS
PubMed
Google Scholar
R. Khandia, A. Sharma, T. Alqahtani, A.M. Alqahtani, Y.I. Asiri, S. Alqahtani, A.M. Alharbi, M.A. Kamal, Strong Selectional Forces Fine-Tune CpG Content in Genes Involved in Neurological Disorders as Revealed by Codon Usage Patterns, Frontiers in Neuroscience. 16 (2022). https://www.frontiersin.org/article/https://doi.org/10.3389/fnins.2022.887929 (accessed June 16, 2022).
Cardon LR, Burge C, Clayton DA, Karlin S. Pervasive CpG suppression in animal mitochondrial genomes. Proc Natl Acad Sci U S A. 1994;91:3799–803. https://doi.org/10.1073/pnas.91.9.3799.
Article
CAS
PubMed
PubMed Central
Google Scholar
Kunec D, Osterrieder N. Codon pair bias is a direct consequence of dinucleotide bias. Cell Rep. 2016;14:55–67. https://doi.org/10.1016/j.celrep.2015.12.011.
Article
CAS
PubMed
Google Scholar
Bestor TH. The DNA methyltransferases of mammals. Hum Mol Genet. 2000;9:2395–402. https://doi.org/10.1093/hmg/9.16.2395.
Article
CAS
PubMed
Google Scholar
Bauer AP, Leikam D, Krinner S, Notka F, Ludwig C, Längst G, Wagner R. The impact of intragenic CpG content on gene expression. Nucleic Acids Res. 2010;38:3891–908. https://doi.org/10.1093/nar/gkq115.
Article
CAS
PubMed
PubMed Central
Google Scholar
Saxonov S, Berg P, Brutlag DL. A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters. Proc Natl Acad Sci U S A. 2006;103:1412–7. https://doi.org/10.1073/pnas.0510310103.
Article
CAS
PubMed
PubMed Central
Google Scholar
Beutler E, Gelbart T, Han JH, Koziol JA, Beutler B. Evolution of the genome and the genetic code: selection at the dinucleotide level by methylation and polyribonucleotide cleavage. Proc Natl Acad Sci U S A. 1989;86:192–6. https://doi.org/10.1073/pnas.86.1.192.
Article
CAS
PubMed
PubMed Central
Google Scholar
Paul P, Malakar AK, Chakraborty S. Codon usage vis-a-vis start and stop codon context analysis of three dicot species. J Genet. 2018;97:97–107.
Article
CAS
PubMed
Google Scholar
Munjal A, Khandia R, Shende KK, Das J. Mycobacterium lepromatosis genome exhibits unusually high CpG dinucleotide content and selection is key force in shaping codon usage. Infect Genet Evol. 2020;84: 104399. https://doi.org/10.1016/j.meegid.2020.104399.
Article
CAS
PubMed
Google Scholar
A.K. Malakar, B. Halder, P. Paul, H. Deka, S. Chakraborty, Genetic evolution and codon usage analysis of NKX-2.5 gene governing heart development in some mammals, Genomics. 112 (2020) 1319–1329. https://doi.org/10.1016/j.ygeno.2019.07.023.
A. Wibowo, Phylogeography and Proline amino acid usage of Asian tiger mosquito Aedes albopictus (Skuse 1894) populations along landscape gradients in Indonesia, 2021. https://doi.org/10.1101/2021.03.14.435316.
H. Bordoloi, S. Nirmala, Codon usage bias analysis of genes linked with esophagus cancer, Biomedical Informatics. (2021) 10.
Almutairi MM, Alrajhi AA. Prediction of gene expression under drought stress in spring wheat using codon usage pattern, Saudi. J Biol Sci. 2021;28:4000–4. https://doi.org/10.1016/j.sjbs.2021.04.015.
Article
CAS
Google Scholar
Chakraborty S, Barbhuiya PA, Paul S, Uddin A, Choudhury Y, Ahn Y, Cho YS. Codon usage trend in genes associated with obesity. Biotechnol Lett. 2020;42:1865–75. https://doi.org/10.1007/s10529-020-02931-z.
Article
CAS
PubMed
Google Scholar
Yang Q, Yu C-H, Zhao F, Dang Y, Wu C, Xie P, Sachs MS, Liu Y. eRF1 mediates codon usage effects on mRNA translation efficiency through premature termination at rare codons. Nucleic Acids Res. 2019;47:9243–58. https://doi.org/10.1093/nar/gkz710.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bulmer M. The selection-mutation-drift theory of synonymous codon usage. Genetics. 1991;129:897–907. https://doi.org/10.1093/genetics/129.3.897.
Article
CAS
PubMed
PubMed Central
Google Scholar
Marais G, Mouchiroud D, Duret L. Does recombination improve selection on codon usage? Lessons from nematode and fly complete genomes, Proc Natl Acad Sci U S A. 2001;98:5688–92. https://doi.org/10.1073/pnas.091427698.
Article
CAS
PubMed
Google Scholar
Duret L, Mouchiroud D. Expression pattern and surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis. Proc Natl Acad Sci U S A. 1999;96:4482–7. https://doi.org/10.1073/pnas.96.8.4482.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chu D, Wei L. Direct in vivo observation of the effect of codon usage bias on gene expression in Arabidopsis hybrids. J Plant Physiol. 2021;265: 153490. https://doi.org/10.1016/j.jplph.2021.153490.
Article
CAS
PubMed
Google Scholar
Pouyet F, Mouchiroud D, Duret L, Sémon M. Recombination, meiotic expression and human codon usage. Elife. 2017;6: e27344. https://doi.org/10.7554/eLife.27344.
Article
PubMed
PubMed Central
Google Scholar
Angellotti MC, Bhuiyan SB, Chen G, Wan X-F. CodonO: codon usage bias analysis within and across genomes. Nucleic Acids Res. 2007;35:W132-136. https://doi.org/10.1093/nar/gkm392.
Article
PubMed
PubMed Central
Google Scholar
Rao Y, Wu G, Wang Z, Chai X, Nie Q, Zhang X. Mutation bias is the driving force of codon usage in the Gallus gallus genome. DNA Res. 2011;18:499–512. https://doi.org/10.1093/dnares/dsr035.
Article
CAS
PubMed
PubMed Central
Google Scholar
Tao P, Dai L, Luo M, Tang F, Tien P, Pan Z. Analysis of synonymous codon usage in classical swine fever virus. Virus Genes. 2009;38:104–12. https://doi.org/10.1007/s11262-008-0296-z.
Article
CAS
PubMed
Google Scholar
Liu H, He R, Zhang H, Huang Y, Tian M, Zhang J. Analysis of synonymous codon usage in Zea mays. Mol Biol Rep. 2010;37:677–84. https://doi.org/10.1007/s11033-009-9521-7.
Article
CAS
PubMed
Google Scholar
Das JK, Roy S. Comparative analysis of human coronaviruses focusing on nucleotide variability and synonymous codon usage patterns. Genomics. 2021;113:2177–88. https://doi.org/10.1016/j.ygeno.2021.05.008.
Article
CAS
PubMed
Google Scholar
Majewski J. Dependence of mutational asymmetry on gene-expression levels in the human genome. Am J Hum Genet. 2003;73:688–92. https://doi.org/10.1086/378134.
Article
CAS
PubMed
PubMed Central
Google Scholar
Elhaik E, Pellegrini M, Tatarinova TV. Gene expression and nucleotide composition are associated with genic methylation level in Oryza sativa. BMC Bioinformatics. 2014;15:23. https://doi.org/10.1186/1471-2105-15-23.
Article
PubMed
PubMed Central
Google Scholar
Bessière C, Taha M, Petitprez F, Vandel J, Marin J-M, Bréhélin L, Lèbre S, Lecellier C-H. Probing instructions for expression regulation in gene nucleotide compositions. PLoS Comput Biol. 2018;14: e1005921. https://doi.org/10.1371/journal.pcbi.1005921.
Article
CAS
PubMed
PubMed Central
Google Scholar
Halder B, Malakar AK, Chakraborty S. Nucleotide composition determines the role of translational efficiency in human genes. Bioinformation. 2017;13:46–53. https://doi.org/10.6026/97320630013046.
Article
PubMed
PubMed Central
Google Scholar
Lynch M. The frailty of adaptive hypotheses for the origins of organismal complexity. Proc Natl Acad Sci U S A. 2007;104(Suppl 1):8597–604. https://doi.org/10.1073/pnas.0702207104.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lassalle F, Périan S, Bataillon T, Nesme X, Duret L, Daubin V. GC-Content evolution in bacterial genomes: the biased gene conversion hypothesis expands. PLoS Genet. 2015;11: e1004941. https://doi.org/10.1371/journal.pgen.1004941.
Article
CAS
PubMed
PubMed Central
Google Scholar
Oldfield CJ, Peng Z, Uversky VN, Kurgan L. Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins. Cell Mol Life Sci. 2020;77:149–60. https://doi.org/10.1007/s00018-019-03166-6.
Article
CAS
PubMed
Google Scholar
Romero P, Obradovic Z, Li X, Garner EC, Brown CJ, Dunker AK. Sequence complexity of disordered protein. Proteins. 2001;42:38–48. https://doi.org/10.1002/1097-0134(20010101)42:1%3c38::aid-prot50%3e3.0.co;2-3.
Article
CAS
PubMed
Google Scholar
Henry I, Sharp PM. Predicting gene expression level from codon usage bias. Mol Biol Evol. 2007;24:10–2. https://doi.org/10.1093/molbev/msl148.
Article
CAS
PubMed
Google Scholar
P. Gaspar, J. Luís Oliveira, J. Frommlet, M.A.S. Santos, G. Moura, EuGene: maximizing synthetic gene design for heterologous expression, Bioinformatics. 32 (2016) 1120. https://doi.org/10.1093/bioinformatics/btw063.
Song H, Liu J, Song Q, Zhang Q, Tian P, Nan Z. Comprehensive analysis of codon usage bias in seven epichloë species and their peramine-coding genes. Front Microbiol. 2017;8:1419. https://doi.org/10.3389/fmicb.2017.01419.
Article
PubMed
PubMed Central
Google Scholar
Frank MG, Barrientos RM, Biedenkapp JC, Rudy JW, Watkins LR, Maier SF. mRNA up-regulation of MHC II and pivotal pro-inflammatory genes in normal brain aging. Neurobiol Aging. 2006;27:717–22. https://doi.org/10.1016/j.neurobiolaging.2005.03.013.
Article
CAS
PubMed
Google Scholar
Uddin A, Paul N, Chakraborty S. The codon usage pattern of genes involved in ovarian cancer. Ann N Y Acad Sci. 2019;1440:67–78. https://doi.org/10.1111/nyas.14019.
Article
CAS
PubMed
Google Scholar
Morton BR. The role of context-dependent mutations in generating compositional and codon usage bias in grass chloroplast DNA. J Mol Evol. 2003;56:616–29. https://doi.org/10.1007/s00239-002-2430-1.
Article
CAS
PubMed
Google Scholar
Sharp PM, Li WH. The codon adaptation index–a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res. 1987;15:1281–95. https://doi.org/10.1093/nar/15.3.1281.
Article
CAS
PubMed
PubMed Central
Google Scholar
G Ata H Wang H Bai X Yao S Tao 2021 Edging on Mutational Bias Induced Natural Selection From Host and Natural Reservoirs Predominates Codon Usage Evolution in Hantaan Virus, Front Microbiol 12 69978810.3389/fmicb.2021.699788
Encyclopedia of Evolutionary Biology || Codon Usage and Translational Selection | Hershberg, R. | download, (n.d.). https://ur.booksc.me/book/62640174/c6d537 (accessed December 3, 2021).
Wu G, Nie L, Zhang W. Predicted highly expressed genes in Nocardia farcinica and the implication for its primary metabolism and nocardial virulence. Antonie Van Leeuwenhoek. 2006;89:135–46. https://doi.org/10.1007/s10482-005-9016-z.
Article
CAS
PubMed
Google Scholar
Bourret J, Alizon S, Bravo IG. COUSIN (COdon Usage Similarity INdex): a normalized measure of codon usage preferences. Genome Biol Evol. 2019;11:3523–8. https://doi.org/10.1093/gbe/evz262.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shields DC, Sharp PM, Higgins DG, Wright F. “Silent” sites in Drosophila genes are not neutral: evidence of selection among synonymous codons. Mol Biol Evol. 1988;5:704–16. https://doi.org/10.1093/oxfordjournals.molbev.a040525.
Article
CAS
PubMed
Google Scholar
Wright F. The “effective number of codons” used in a gene. Gene. 1990;87:23–9. https://doi.org/10.1016/0378-1119(90)90491-9.
Article
CAS
PubMed
Google Scholar
McWeeney SK, Valdes AM. Codon usage bias and base composition in MHC genes in humans and common chimpanzees. Immunogenetics. 1999;49:272–9. https://doi.org/10.1007/s002510050493.
Article
CAS
PubMed
Google Scholar
Lu J, Salzberg SL. SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes. PLoS Comput Biol. 2020;16: e1008439. https://doi.org/10.1371/journal.pcbi.1008439.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lobry JR. Asymmetric substitution patterns in the two DNA strands of bacteria. Mol Biol Evol. 1996;13:660–5. https://doi.org/10.1093/oxfordjournals.molbev.a025626.
Article
CAS
PubMed
Google Scholar
Freeman JM, Plasterer TN, Smith TF, Mohr SC. Patterns of genome organization in Bacteria. Science. 1998;279:1827–1827. https://doi.org/10.1126/science.279.5358.1827a.
Article
Google Scholar