Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm
The Wallace H. Coulter Department of Biomedical Engineering · Georgia Institute of Technology · +1 more institution
Abstract
We present a new approach to automatic training of a eukaryotic ab initio gene finding algorithm. With the advent of Next-Generation Sequencing, automatic training has become paramount, allowing genome annotation pipelines to keep pace with the speed of genome sequencing. Earlier we developed GeneMark-ES, currently the only gene finding algorithm for eukaryotic genomes that performs automatic training in unsupervised ab initio mode. The new algorithm, GeneMark-ET augments GeneMark-ES with a novel method that integrates RNA-Seq read alignments into the self-training procedure. Use of 'assembled' RNA-Seq transcripts is far from trivial; significant error rate of assembly was revealed in recent assessments. We…
Citation impact
- FWCI
- 4.69
- Percentile
- 100%
- References
- 26
Authors
3- ALAlexandre Lomsadze
The Wallace H. Coulter Department of Biomedical Engineering
- PBPaul Burns
The Wallace H. Coulter Department of Biomedical Engineering
- MBMark BorodovskyCorresponding
Georgia Institute of Technology, Moscow Institute of Physics and Technology, The Wallace H. Coulter Department of Biomedical Engineering
Topics & keywords
- Gene prediction
- Biology
- Genome
- Computational biology
- Annotation
- Gene
- RNA-Seq
- Gene Annotation