[1]
Y. Wang, P.Y. Qian, Conservative fragments in bacterial 16S rRNA genes and primer design for 16S ribosomal DNA amplicons in metagenomic studies, PLoS One. 4(2009) e7401.
DOI: 10.1371/journal.pone.0007401
Google Scholar
[2]
R. Sipos, A.J. Székely, M. Palatinszky, S. Révész, K. Márialigeti, M. Nikolausz, Effect of primer mismatch, annealing temperature and PCR cycle number on 16S rRNA gene-targetting bacterial community analysis, FEMS Microbiol. Ecol. 60 (2007).
DOI: 10.1111/j.1574-6941.2007.00283.x
Google Scholar
[3]
M.L. Sogin, H.G. Morrison, J.A. Huber, D. Mark Welch, S.M. Huse, P.R. Neal, J.M. Arrieta, G.J. Herndl, Microbial diversity in the deep sea and the underexplored rare biosphere, Proc. Natl. Acad. Sci. U. S. A. 103 (2006) 12115-12120.
DOI: 10.1073/pnas.0605127103
Google Scholar
[4]
S.K. Ames, D.A. Hysom, S.N. Gardner, G.S. Lloyd, M.B. Gokhale, J.E. Allen, Scalable metagenomic taxonomy classification using a reference genome database, Bioinformatics. 29 (2013) 2253-2260.
DOI: 10.1093/bioinformatics/btt389
Google Scholar
[5]
K. Břinda, M. Sykulski, G. Kucherov, Spaced seeds improve k-mer-based metagenomic classification, Bioinformatics. 31 (2015) 3584-3592.
DOI: 10.1093/bioinformatics/btv419
Google Scholar
[6]
S.S. Minot, N. Krumm, N. B. Greenfield, One Codex: A Sensitive and Accurate Data Platform for Genomic Microbial Identification. bioRxiv (2015) 027607. doi: https: /doi. org/10. 1101/027607.
DOI: 10.1101/027607
Google Scholar
[7]
M. Acosta, P. Galleguillos, Y. Ghorbani, P. Tapia, Y. Contador, A. Velásquez, C. Espoz, C. Pinilla, C. Demergasso, Variation in microbial community from predominantly mesophilic to thermotolerant and moderately thermophilic species in an industrial copper heap bioleaching operation, Hydrometallurgy. 150 (2014).
DOI: 10.1016/j.hydromet.2014.09.010
Google Scholar
[8]
S. Marín, M. Acosta, P. Galleguillos, Y. Villegas, D. Cautivo, V. Zepeda, C. Demergasso, Transcriptional dynamics study of Calvin-Benson- Bassham (CBB) genes in Acidithiobacillus thiooxidans growing under different carbon dioxide availability: submitted to Solid State Phenomena (2017).
DOI: 10.4028/www.scientific.net/ssp.262.376
Google Scholar
[9]
X. Zhang, J. Niu, Y. Liang, X. Liu, H. Yin, Metagenome-scale analysis yields insights into the structure and function of microbial communities in a copper bioleaching heap. BMC Genet. 17 (2016) 21. doi: 10. 1186/s12863-016-0330-4.
DOI: 10.1186/s12863-016-0330-4
Google Scholar
[10]
Y. Xiao, X. Liu, L. Ma, Y. Liang, J. Niu, Y. Gu, X. Zhang, X. Hao, W. Dong, S. She, H. Yin, Microbial communities from different subsystems in biological heap leaching system play different roles in iron and sulfur metabolisms, Appl. Microbiol. Biotechnol. 100 (2016).
DOI: 10.1007/s00253-016-7537-1
Google Scholar
[11]
X. Liu, B. Chen, J. Chen, M. Zhang, J. Wen, D. Wang, R. Ruan, Spatial variation of microbial community structure in the Zijinshan commercial copper heap bioleaching plant, Miner. Eng. 94 (2016) 76-82.
DOI: 10.1016/j.mineng.2016.05.008
Google Scholar
[12]
Y. Jia, H. Sun, D. Chen, H. Gao, R. Ruan, Characterization of microbial community in industrial bioleaching heap of copper sulfide ore at Monywa mine, Myanmar, Hydrometallurgy. 164 (2016) 355-361.
DOI: 10.1016/j.hydromet.2016.07.007
Google Scholar
[13]
A.P. Yelton, B.C. Thomas, S.L. Simmons, P. Wilmes, A. Zemla, M.P. Thelen,N. Justice, J.F. Banfield, A semi-quantitative, synteny-based method to improve functional predictions for hypothetical and poorly annotated bacterial and archaeal genes. PLoS Comput. Biol. 7 (2011).
DOI: 10.1371/journal.pcbi.1002230
Google Scholar