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Common integration sites of published datasets identified using a graph-based framework
- Source :
- Computational and Structural Biotechnology Journal, Computational and Structural Biotechnology Journal, Vol 14, Iss C, Pp 87-90 (2016)
- Publication Year :
- 2015
- Publisher :
- Research Network of Computational and Structural Biotechnology, 2015.
-
Abstract
- With next-generation sequencing, the genomic data available for the characterization of integration sites (IS) has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF) from our previous article, in which a collection of common integration sites (CIS) was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.
- Subjects :
- 0301 basic medicine
Bioinformatics
Computer science
Genomic data
lcsh:Biotechnology
Short Communication
Biophysics
computer.software_genre
Biochemistry
Genome
03 medical and health sciences
Structural Biology
lcsh:TP248.13-248.65
Genetics
Integrational Mutagenesis Analysis
Workflow design
Systems Biology
Graph based
Computational Biology
Gene Therapy
Graph
Computer Science Applications
030104 developmental biology
Viral integration
Data mining
computer
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 20010370
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- Computational and Structural Biotechnology Journal
- Accession number :
- edsair.doi.dedup.....6c8353119d94d23019137db4823285a5