Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
about
Parallel computing in genomic research: advances and applicationsThe odorant receptor co-receptor from the bed bug, Cimex lectularius LNext-generation sequencing approach for connecting secondary metabolites to biosynthetic gene clusters in fungiThe real cost of sequencing: scaling computation to keep pace with data generationKarect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data.Assessment of de novo assemblers for draft genomes: a case study with fungal genomesCompacting de Bruijn graphs from sequencing data quickly and in low memoryLightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads.Indel Group in Genomes (IGG) Molecular Genetic Markers.
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P2860
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
description
2013 nî lūn-bûn
@nan
2013 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
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2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
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name
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@ast
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@en
type
label
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@ast
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@en
prefLabel
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@ast
Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@en
P2860
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Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures
@en
P2860
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P356
10.1371/JOURNAL.PONE.0075505
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2013-09-27T00:00:00Z