2008
DOI: 10.1016/j.plaphy.2008.05.009
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Identification of micro-RNAs in cotton

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Cited by 64 publications
(53 citation statements)
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“…The filter is composed of four indices, namely GC content, core mfe, hairpin mfe and the ratio of core mfe to hairpin mfe (ch_ratio) (Barozai et al, 2008). As shown in (Table # 2 [19] and Barozai et al [11].…”
Section: Sequence and Structural Features Filtermentioning
confidence: 99%
“…The filter is composed of four indices, namely GC content, core mfe, hairpin mfe and the ratio of core mfe to hairpin mfe (ch_ratio) (Barozai et al, 2008). As shown in (Table # 2 [19] and Barozai et al [11].…”
Section: Sequence and Structural Features Filtermentioning
confidence: 99%
“…The parameters were adjusted same as reported earlier [21]. The stem portion of the hairpin checked for the mature sequences with at least 12 base pairs involved in Watson-Crick or G/U base pairing between the mature miRNA and the opposite strand (miRNA*).…”
Section: Creation Of Hairpin Structuresmentioning
confidence: 99%
“…To validate the miRNAs through the sequence and structural features filter, the GC content, Core mfe, hairpin mfe and Ch_ratio were calculated as described by Li et al, (2006) [27] with a little modification for Core mfe calculation, as described by Barozai et al, (2008) [21]. The mfe for core and hairpin structures were calculated by MFOLD (version3.2) [26] publicly available at http://www.bioinfo.rpi.edu/applications/mfold/ rna/form1.cgi.…”
Section: Sequence and Structural Features Filtrationmentioning
confidence: 99%
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“…The length of the precursor miRNAs ranged from 93 to 194 nt with an average of 133 nt. The newly identified precursor miRNAs have minimum folding free energies (MFE) ranging from -74 to -162 kcal/mol which are not in consistence with folding energies of tRNA -275 kcal /mol and rRNA -33 kcal/ mol (Barozai et al, 2008). The Minimal folding free energy index (MFEI) and MFE have been considered as significant features that distinguish miRNAs from other non coding RNAs (rRNA, tRNA, mRNA).…”
Section: In Silico Identification Of Novel Mirnamentioning
confidence: 99%