1. ZHAW digitalcollection
  2. Life Sciences und Facility Management
  3. Publikationen
  4. Publikationen Life Sciences und Facility Management
Full metadata record
DC FieldValueLanguage
dc.contributor.authorOstash, Bohdan-
dc.contributor.authorAnisimova, Maria-
dc.date.accessioned2020-03-05T10:22:06Z-
dc.date.available2020-03-05T10:22:06Z-
dc.date.issued2020-
dc.identifier.isbn978-981-15-2445-5de_CH
dc.identifier.isbn978-981-15-2444-8de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/19602-
dc.description.abstractCost and time of genome sequencing have plummeted over the last decade. This leads to explosive growth of genetic databases and development of novel sequencing-based approaches to study various biological phenomena. The database growth was particularly beneficial for investigation of protein-coding sequences at the codon level, requiring the access to large sets of related genomes. Such studies are expected to illuminate biological forces that shape primary structure of coding sequences and predict their evolutionary trajectories more precisely. In addition to fundamental interest, codon usage studies are of ample practical value, for example, in drug discovery and genomic medicine areas. Nevertheless, the depth of our understanding of codon-related issues is currently shallower as compared to what we know about nucleotide and amino acid sequences. Besides the lack of adequate datasets in the early days of molecular biology, codon usage studies, in our opinion, suffer from underdevelopment of easy-to-use tools to analyze and visualize how codon sequence changes along the gene and across the homologous genes in course of evolution. In this review, we aim to describe main areas of codon usage studies with an emphasis on the tools that allow visual interpretation of the data. We discuss underlying principles of different approaches, what kind of statistics lends confidence in their results and what has to be done to further boost the field of codon usage research.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofStatistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applicationsde_CH
dc.relation.ispartofseriesAlgorithms for Intelligent Systemsde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectGenetic codede_CH
dc.subjectCodon contextde_CH
dc.subjectGeneticsde_CH
dc.subjectEvolutionde_CH
dc.subjectGenede_CH
dc.subjectSequence analysisde_CH
dc.subject.ddc572: Biochemiede_CH
dc.titleVisualizing codon usage within and across genomes : concepts and toolsde_CH
dc.typeBuchbeitragde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
zhaw.publisher.placeSingaporede_CH
dc.identifier.doi10.1007/978-981-15-2445-5_13de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end288de_CH
zhaw.pages.start213de_CH
zhaw.parentwork.editorSrinivasa, K. G.-
zhaw.parentwork.editorSiddesh, G. M.-
zhaw.parentwork.editorManisekhar, S. R.-
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewEditorial reviewde_CH
zhaw.funding.snf182330de_CH
zhaw.webfeedComputational Genomicsde_CH
zhaw.funding.zhawThe effect of programmed ribosomal frameshifting on codon usage biasde_CH
zhaw.author.additionalNode_CH
Appears in collections:Publikationen Life Sciences und Facility Management

Files in This Item:
There are no files associated with this item.
Show simple item record
Ostash, B., & Anisimova, M. (2020). Visualizing codon usage within and across genomes : concepts and tools. In K. G. Srinivasa, G. M. Siddesh, & S. R. Manisekhar (Eds.), Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications (pp. 213–288). Springer. https://doi.org/10.1007/978-981-15-2445-5_13
Ostash, B. and Anisimova, M. (2020) ‘Visualizing codon usage within and across genomes : concepts and tools’, in K.G. Srinivasa, G.M. Siddesh, and S.R. Manisekhar (eds) Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications. Singapore: Springer, pp. 213–288. Available at: https://doi.org/10.1007/978-981-15-2445-5_13.
B. Ostash and M. Anisimova, “Visualizing codon usage within and across genomes : concepts and tools,” in Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications, K. G. Srinivasa, G. M. Siddesh, and S. R. Manisekhar, Eds. Singapore: Springer, 2020, pp. 213–288. doi: 10.1007/978-981-15-2445-5_13.
OSTASH, Bohdan und Maria ANISIMOVA, 2020. Visualizing codon usage within and across genomes : concepts and tools. In: K. G. SRINIVASA, G. M. SIDDESH und S. R. MANISEKHAR (Hrsg.), Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications. Singapore: Springer. S. 213–288. ISBN 978-981-15-2445-5
Ostash, Bohdan, and Maria Anisimova. 2020. “Visualizing Codon Usage within and across Genomes : Concepts and Tools.” In Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications, edited by K. G. Srinivasa, G. M. Siddesh, and S. R. Manisekhar, 213–88. Singapore: Springer. https://doi.org/10.1007/978-981-15-2445-5_13.
Ostash, Bohdan, and Maria Anisimova. “Visualizing Codon Usage within and across Genomes : Concepts and Tools.” Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications, edited by K. G. Srinivasa et al., Springer, 2020, pp. 213–88, https://doi.org/10.1007/978-981-15-2445-5_13.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.