LEADER 02237nam  2200373z- 450 
001 9910220053503321
005 20231214133002.0
035   $a(CKB)3800000000216243
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/54590
035   $a(EXLCZ)993800000000216243
100   $a20202102d2016      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aNew Insights into Microbial Ecology through Subtle Nucleotide Variation
210   $cFrontiers Media SA$d2016
215   $a1 electronic resource (133 p.)
225 1 $aFrontiers Research Topics
311   $a2-88919-988-6 
330   $aThe 16S ribosomal RNA gene commonly serves as a molecular marker for investigating microbial community composition and structure. Vast amounts of 16S rRNA amplicon data generated from environmental samples thanks to the recent advances in sequencing technologies allowed microbial ecologists to explore microbial community dynamics over temporal and spatial scales deeper than ever before. However, widely used methods for the analysis of bacterial communities generally ignore subtle nucleotide variations among high-throughput sequencing reads and often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial datasets. Lack of proper partitioning of the sequencing data into relevant units often masks important ecological patterns. Our research topic contains articles that use oligotyping to demonstrate the importantance of high-resolution analyses of marker gene data, and providides further evidence why microbial ecologists should open the "black box" of OTUs identified through arbitrary sequence similarity thresholds.
610   $ahigh-resolution
610   $aoligotyping
610   $aMinimum Entropy Decomposition
610   $amicrobiome
610   $a16S rRNA gene
700   $aA. Murat Eren$4auth$01286185
702   $aMitchell Sogin$4auth
702   $aLois Maignien$4auth
906   $aBOOK
912   $a9910220053503321
996   $aNew Insights into Microbial Ecology through Subtle Nucleotide Variation$93019751
997   $aUNINA