Faculty, Staff and Student Publications
Publication Date
3-18-2022
Journal
STAR Protocols
Abstract
Even though there were many tool developments of fusion gene prediction from NGS data, too many false positives are still an issue. Wise use of the genomic features around the fusion gene breakpoints will be helpful to identify reliable fusion genes efficiently. For this aim, we developed FusionAI, a deep learning pipeline predicting human fusion gene breakpoints from DNA sequence. FusionAI is freely available via https://compbio.uth.edu/FusionGDB2/FusionAI. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021b).
Keywords
DNA, Deep Learning, Gene Fusion, Genomics, Humans, Bioinformatics, Health Sciences, Genomics, Molecular Biology, Computer sciences
DOI
10.1016/j.xpro.2022.101185
PMID
35252882
PMCID
PMC8892011
PubMedCentral® Posted Date
2-28-2022
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Graphical Abstract
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Computer Sciences Commons, Data Science Commons, Medical Genetics Commons, Medical Molecular Biology Commons
