CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses

Chuanyi Zhang; Palash Sashittal; Mohammed El-Kebir

doi:10.1007/978-3-031-04749-7_28

CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses

Chuanyi Zhang, Palash Sashittal, Mohammed El-Kebir

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Coronaviruses are comprised of a single-stranded RNA genome that is ready to be translated by the host ribosome.

Original language	English (US)
Title of host publication	Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings
Editors	Itsik Pe’er
Publisher	Springer
Pages	360-362
Number of pages	3
ISBN (Print)	9783031047480
DOIs	https://doi.org/10.1007/978-3-031-04749-7_28
State	Published - 2022
Event	26th International Conference on Research in Computational Molecular Biology, RECOMB 2022 - San Diego, United States Duration: May 22 2022 → May 25 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13278 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	26th International Conference on Research in Computational Molecular Biology, RECOMB 2022
Country/Territory	United States
City	San Diego
Period	5/22/22 → 5/25/22

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Online availability

10.1007/978-3-031-04749-7_28

Library availability

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Cite this

Zhang, C., Sashittal, P., & El-Kebir, M. (2022). CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. In I. Pe’er (Ed.), Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings (pp. 360-362). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13278 LNBI). Springer. https://doi.org/10.1007/978-3-031-04749-7_28

CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. / Zhang, Chuanyi; Sashittal, Palash; El-Kebir, Mohammed.
Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings. ed. / Itsik Pe’er. Springer, 2022. p. 360-362 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13278 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, C, Sashittal, P & El-Kebir, M 2022, CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. in I Pe’er (ed.), Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13278 LNBI, Springer, pp. 360-362, 26th International Conference on Research in Computational Molecular Biology, RECOMB 2022, San Diego, United States, 5/22/22. https://doi.org/10.1007/978-3-031-04749-7_28

Zhang C, Sashittal P, El-Kebir M. CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. In Pe’er I, editor, Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings. Springer. 2022. p. 360-362. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-04749-7_28

Zhang, Chuanyi ; Sashittal, Palash ; El-Kebir, Mohammed. / CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings. editor / Itsik Pe’er. Springer, 2022. pp. 360-362 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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