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DeepRibo : a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns

Jim Clauwaert (UGent) , Gerben Menschaert (UGent) and Willem Waegeman (UGent)
(2019) NUCLEIC ACIDS RESEARCH. 47(6).
Author
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Abstract
Annotation of gene expression in prokaryotes of-ten finds itself corrected due to small variations ofthe annotated gene regions observed between differ-ent (sub)-species. It has become apparent that tradi-tional sequence alignment algorithms, used for thecuration of genomes, are not able to map the fullcomplexity of the genomic landscape. We presentDeepRibo, a novel neural network utilizing featuresextracted from ribosome profiling information andbinding site sequence patterns that shows to be aprecise tool for the delineation and annotation of ex-pressed genes in prokaryotes. The neural networkcombines recurrent memory cells and convolutionallayers, adapting the information gained from boththe high-throughput ribosome profiling data and ri-bosome binding translation initiation sequence re-gion into one model. DeepRibo is designed as a sin-gle model trained on a variety of ribosome profil-ing experiments, used for the identification of openreading frames in prokaryotes withoutaprioriknowl-edge of the translational landscape. Through exten-sive validation of the model trained on various setsof data, multiple species sequence similarity, massspectrometry and Edman degradation verified pro-teins, the effectiveness of DeepRibo is highlighted.
Keywords
TRANSLATION INITIATION SITES, START SITES, IDENTIFICATION, REVEALS, COMPLEXITY, PROTEOMICS, LANDSCAPE, CELLS

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MLA
Clauwaert, Jim, et al. “DeepRibo : A Neural Network for Precise Gene Annotation of Prokaryotes by Combining Ribosome Profiling Signal and Binding Site Patterns.” NUCLEIC ACIDS RESEARCH, vol. 47, no. 6, 2019, doi:10.1093/nar/gkz061.
APA
Clauwaert, J., Menschaert, G., & Waegeman, W. (2019). DeepRibo : a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns. NUCLEIC ACIDS RESEARCH, 47(6). https://doi.org/10.1093/nar/gkz061
Chicago author-date
Clauwaert, Jim, Gerben Menschaert, and Willem Waegeman. 2019. “DeepRibo : A Neural Network for Precise Gene Annotation of Prokaryotes by Combining Ribosome Profiling Signal and Binding Site Patterns.” NUCLEIC ACIDS RESEARCH 47 (6). https://doi.org/10.1093/nar/gkz061.
Chicago author-date (all authors)
Clauwaert, Jim, Gerben Menschaert, and Willem Waegeman. 2019. “DeepRibo : A Neural Network for Precise Gene Annotation of Prokaryotes by Combining Ribosome Profiling Signal and Binding Site Patterns.” NUCLEIC ACIDS RESEARCH 47 (6). doi:10.1093/nar/gkz061.
Vancouver
1.
Clauwaert J, Menschaert G, Waegeman W. DeepRibo : a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns. NUCLEIC ACIDS RESEARCH. 2019;47(6).
IEEE
[1]
J. Clauwaert, G. Menschaert, and W. Waegeman, “DeepRibo : a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns,” NUCLEIC ACIDS RESEARCH, vol. 47, no. 6, 2019.
@article{8617668,
  abstract     = {{Annotation of gene expression in prokaryotes of-ten finds itself corrected due to small variations ofthe annotated gene regions observed between differ-ent (sub)-species. It has become apparent that tradi-tional sequence alignment algorithms, used for thecuration of genomes, are not able to map the fullcomplexity of the genomic landscape. We presentDeepRibo, a novel neural network utilizing featuresextracted from ribosome profiling information andbinding site sequence patterns that shows to be aprecise tool for the delineation and annotation of ex-pressed genes in prokaryotes. The neural networkcombines recurrent memory cells and convolutionallayers, adapting the information gained from boththe high-throughput ribosome profiling data and ri-bosome binding translation initiation sequence re-gion into one model. DeepRibo is designed as a sin-gle model trained on a variety of ribosome profil-ing experiments, used for the identification of openreading frames in prokaryotes withoutaprioriknowl-edge of the translational landscape. Through exten-sive validation of the model trained on various setsof data, multiple species sequence similarity, massspectrometry and Edman degradation verified pro-teins, the effectiveness of DeepRibo is highlighted.}},
  articleno    = {{e36}},
  author       = {{Clauwaert, Jim and Menschaert, Gerben and Waegeman, Willem}},
  issn         = {{0305-1048}},
  journal      = {{NUCLEIC ACIDS RESEARCH}},
  keywords     = {{TRANSLATION INITIATION SITES,START SITES,IDENTIFICATION,REVEALS,COMPLEXITY,PROTEOMICS,LANDSCAPE,CELLS}},
  language     = {{eng}},
  number       = {{6}},
  title        = {{DeepRibo : a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns}},
  url          = {{http://doi.org/10.1093/nar/gkz061}},
  volume       = {{47}},
  year         = {{2019}},
}
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