Cargando…
A de novo next generation genomic sequence assembler based on string graph and MapReduce cloud computing framework
BACKGROUND: State-of-the-art high-throughput sequencers, e.g., the Illumina HiSeq series, generate sequencing reads that are longer than 150 bp up to a total of 600 Gbp of data per run. The high-throughput sequencers generate lengthier reads with greater sequencing depth than those generated by prev...
Autores principales: | Chang, Yu-Jung, Chen, Chien-Chih, Chen, Chuen-Liang, Ho, Jan-Ming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521391/ https://www.ncbi.nlm.nih.gov/pubmed/23282094 http://dx.doi.org/10.1186/1471-2164-13-S7-S28 |
Ejemplares similares
-
Subset selection of high-depth next generation sequencing reads for de novo genome assembly using MapReduce framework
por: Fang, Chih-Hao, et al.
Publicado: (2015) -
An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics
por: Taylor, Ronald C
Publicado: (2010) -
Efficient and Scalable Graph Similarity Joins in MapReduce
por: Chen, Yifan, et al.
Publicado: (2014) -
CloudBurst: highly sensitive read mapping with MapReduce
por: Schatz, Michael C.
Publicado: (2009) -
Long Read Alignment with Parallel MapReduce Cloud Platform
por: Al-Absi, Ahmed Abdulhakim, et al.
Publicado: (2015)