Cargando…
Algorithms designed for compressed-gene-data transformation among gene banks with different references
BACKGROUND: With the reduction of gene sequencing cost and demand for emerging technologies such as precision medical treatment and deep learning in genome, it is an era of gene data outbreaks today. How to store, transmit and analyze these data has become a hotspot in the current research. Now the...
Autores principales: | Luo, Qiuming, Guo, Chao, Zhang, Yi Jun, Cai, Ye, Liu, Gang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006589/ https://www.ncbi.nlm.nih.gov/pubmed/29914357 http://dx.doi.org/10.1186/s12859-018-2230-2 |
Ejemplares similares
-
Light-weight reference-based compression of FASTQ data
por: Zhang, Yongpeng, et al.
Publicado: (2015) -
Handling the data management needs of high-throughput sequencing data: SpeedGene, a compression algorithm for the efficient storage of genetic data
por: Qiao, Dandi, et al.
Publicado: (2012) -
Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes
por: Datta, Susmita, et al.
Publicado: (2006) -
Performance evaluation of lossy quality compression algorithms for RNA-seq data
por: Yu, Rongshan, et al.
Publicado: (2020) -
Adapting machine-learning algorithms to design gene circuits
por: Hiscock, Tom W.
Publicado: (2019)