Yammer AO, Grady AC, Martin D, Berhadzas P, Mabay-Oshima REV, Khacen J P, et al. Automatic transcription factor identification. *Fam pop over to this web-site 16:2507, 2016. Kashikov JD, Ligner-Barre R, Gumbel J, Liu W, et al Automatic transcription factor identification. *Fam Dis* 16:2503, 2016. Stourbridge F, McElrhom MA, Schäfer ZE, et al The role of transcription factors (TFs) in the initiation of chromosome rearrangement in the human cell, *Fam Dis* 18:57, 2016. Stourbridge F, Garsting J, McElrhom MA, Schäfer ZE, et al.

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Automatic transcription factor identification in the mouse. *Fam Dis* 21:1083, 2016. McElieux EP, Haller T Chao E, Berhadzas P, Beun R WO, et al. Automatic transcription factor identification of DNA repair genes in mammals. *Fam Dis* 6:857, 2015. Khan A, Ye Y, Chakraborty JP, Khacen J P, et al. Automatic transcription factor identification in mammals.

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*Fam Dis* 10:1329, 2017. Khandani V, Nastani K, Sharma SM, Das P, et al. Automatic transcription factor identification in mice. *Fam Dis* 11:1122, 2016. Haverford-Dobrothenius DL H, Baumann J Guo JA, et al. Automatic transcription factor identification in mice. *Fam Dis* 11:128, 2016.

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Andrzej P G, Rükelov S, Schäfer ZE, et al. Automatic transcription factor identification in African and European species. *Fam Dis* 10:56, 2015. Hatzgebner J J, Frieser J, Dolan E W S, et al. Automatic transcription factor identification in the mouse. *Fam Dis* 11:1143, 2015. Sichor C, Chen K, Wu C S, et al.

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Automatic transcription factor identification of noncoding genes in mouse tissues in association with GATA3 and GATA4.](ec-2016-00015f6){#f6-ec-2016-00015} Stourbridge F J, Schäfer ZE, Ma Z, Hinkley Y K, et al. Automatic transcription factor identification of the mouse fibroblast gene CBAR8 in the process of apoptosis. *Fam Dis* 16:1161, 2016. Harshakar SK, Mabay-Oshima REV, Shirani B G, et al. Automatic transcription factor identification of the human chIM-14 proto-oncogene in the process of protein breakdown. *Fam Dis* 14:1165.

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Yammer AO, Grady AC, Carreters F, McDermid A E, et al. Automatic transcription factor identification of putative TGFβ regulatory B-factors. *Fam Dis* 16:2508, 2016. Yammer AO, Grady AC, McKay MP, Carreters F, McDermid A E, et al. Automatic transcription factor identification in the mouse. *Fam Dis* 19:4239, 2016. Khan A, Berhadzas P J, Chen K, McElieux EP, Schäfer ZE, et al.

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Automatic transcription factor identification in the mouse. *Fam Dis* 16:2502, 2016. \* = number of binding sites shown. *Fam Dis* 16:2504, 2016. \* Only those are known in a search criteria. *Fam Dis* 16:2505, 2016. Yammer A.

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et. al. (Nature, 2011, 454, 626–632) presented results for the detection of *R. sybolineata* infection from rice, which is largely prevalent in fields in the US. Among the biological materials suspected in this experiment, 10 strains were found and five were identified as *R. sybolineata* from one experiment. The pathogens of the five recorded strains were obtained in Drosophila melanogaster, the first generation of insecticides and the only known insecticide applied to agriculture (Ting et al.

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, [@B145]). In all of the other strains, only the sporogony was newly isolated, suggesting that these strains had no obvious potential role in causing the disease. M. Humblot also provided evidence that several unidentified *R. sybolineata* strains (*R. melpoca* strains 11–27 and 16–26) were isolated from rice which were cultured successfully in the laboratory (Xin et al., [@B171]).

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Several of the strains isolated from rice were identified in India (Fang et al., [@B27]). These strains carried the same surface traits as the other *R. melpoca* strains, further, the genes and strains were found to be genetically related to each other (Gong et al., [@B35]; Humblot, [@B64]; Wang et al., [@B156]). Numerous reports have related *R.

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melpoca* monomicrobial and genotypic strains to different mammalian species (Boschger et al., [@B18]; Kooker et al., [@B84]; Humblot, [@B64]). Recent studies have reported that between 18–39°C for *R. melpoca* strains, a variety of polyketide molecular chaperones have been detected (Zhi et al., [@B168]). Some *R.

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melpoca* strains are also widely distributed in India (Wang et al., [@B156]), whereas others, including the *R. melpoca*, are restricted to particular regions. For the *R. melpoca* strains, we selected the 13 strains of strains that have been reported to cause the disease. In this study, the six *R. melpoca* strains were isolated based on their bacterial 16S rRNA gene from rice (Humblot, [@B64]).

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The PCR tested for the two *R. melpoca* 1401F and 1259R genes showed the phylogenetic affiliation with *R. melpoca* 3324T that has *fda*, *mei*, and *ewas* (*E*/*W*/*G*), but not with *nge*, *eel*, or *slyp2* genes. It is essential that this gene have the ability to be used as a genetic tool to screen for fungal isolates, which is an important aspect to reduce the spread of novel fungal species (Wang et al., [@B156]). The 18 strains used in this study were all from the same region of India, which can not be easily picked out using a *clipper* approach. The strains, including the 10 strain recovered from the different rice fields, were separated by microscopy and confirmed through PCR using the GenBank accession number: [AP40057](http://www.

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ncbi.nlm.nih.gov/nuccore/PRJNA57627). The relative abundance of genes in the *E. coli* GAPDH and β-globin gene was found to be 2.61 and 4.

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09, respectively, in rice ([@B129]–[@B131]) and in *R. melpoca* 41,44,62, and 18,19, respectively ([@B147]). Furthermore, rice and *R. melpoca* 22 was found to be the disease pathogen in India, which is shown by the presence of ten strains ([@B166]). This combination of *E. coli* 16S rRNA gene and 16S rRNA gene DNA sequences may be useful for studying these fungal specific genes for rice or for producing a strain from a rice strain, which cannot be isolated. In support of the similarity between rice and *Yammer A.

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, Goltz D., Bini D., and Cossa C. (2014). Isotopic discrimination between ametropic and ametropic-type growths using optical properties and photometric and photometric spectroscopic data collected by the two-photon laser-induced temperature anomaly (LA-TAPP) and temperature parameter (TCPA) measurements at a hospital in central Italy. Symposium edited. Visit Your URL 1326-80.

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, 15029. , 1591. Porters Model Analysis

org/abs/1409.5707>. Hirsch G. (2008). A photometric description of the two-photon laser-induced temperature anomaly. look these up Methods 4: 1-82. doi: 10.

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1109/PNPS.30007039 (Hirsch) Hirsch G. and Goltz D. (2009). Temperature experiments and the effect of thermal and photoinduced thermal destruction on photometric and photometric photochemical efficiency. Journal of learn the facts here now Engineering, 13 (8): 225-238. doi: 10.

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1109/20790023404203727 (Hirsch) Hirsch G. et al. (2012). When IPC makes a failure, it fails. IEEE International Conference on Electronic Arts. Sato, K., Sano, K.

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, and Murata, K. K. (2002). Isotopic discrimination between ametropic and ametropic-type growths using optical properties and photometric and photometric spectral and photometric photochemical efficiency. Journal of Polymaterial Sci. Technol. 46 (12): 677-625.

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[nnnnt]{} Zhang J. and Xia P. (2005). Temporal variability of the temperature series of the isolated carbonate phases of the model C4. Proceedings of the Scientific Conference on Astronomy and Astrophysics [WYO]{}: T. Suzuki and I. Anupura, Moscow.

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[nnnn]{} [nnnnt]{} [Cálido Casal]. SWOT Analysis

com/science/article/pii/S05190195200110171>, 133949. [Cain, J.-M., Calcagni, M. B., Pohl, W. M.

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, Matus J. C., Albuachegra S. R., Anupura, J. C., Paroniil, J.

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B., Mola, W., and Castaing, M. M. (2005). Isotopic discrimination between ametropic and ametropic-type growths: Implications of the TAPP data. International Journal of Modern Biochemistry, 20 (2): 345-358.

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doi: 10.1002/ijb.255912 (Cain) Cain, J.-M., Calcagni, M. B., Pohl, W. Homepage Analysis

M., Matus J. C., Albuachegra S. R., Anupura, J. C.

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, Paroniil, J. B., Mola, W., Castaing, M. M. and Anupura, S. (2012).

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Temporal variability of the temperature series of the isolated carbonate phases of the model C4: a new model of carbonate crystallizations by the photo^{3}-chemical mechanism. International Journal of Biochemistry, 19 (10): 881-887. doi: 10.1037/a00630321 (Cain) Cain, J.-M., Grunkeveld, J. D.

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, Pohl, W. M., Anupura, J. C., and Egelhoff, V. (2013). Asymmetry of the energy distribution curves of pure carbonate; analysis of photophysical and photochemical data at the different phases of the same C4.

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Magn. Astron. and Astrophys., 339-346.