Kaushik, Aman Chandra and Kumar, Ajay and Bharadwaj, Shiv Kumar and Chaudhary, Ravi and Sahi, Shakti (2018) Genomics and proteomics using computational biology. In: Kaushik, Aman Chandra and Kumar, Ajay and Bharadwaj, Shiv and Chaudhary, Ravi and Sahi, Shakti, (eds.) Bioinformatics Techniques for Drug Discovery: Applications for Complex Diseases. SpringerBriefs in Computer Science. Springer Cham, pp. 47-57. ISBN 978-3-319-75731-5 (Print) 978-3-319-75732-2 (Online)
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Official URL: https://dx.doi.org/10.1007/978-3-319-75732-2_8
Abstract
Current functional genomics relies on known and characterised genes, but despite significant efforts in the field of genome annotation, accurate identification and elucidation of protein coding gene structures remains challenging. Methods are limited to computational predictions and transcript-level experimental evidence; hence translation cannot be verified. Proteomic mass spectrometry is a method that enables sequencing of gene product fragments, enabling the validation and refinement of existing gene annotation as well as the elucidation of novel protein coding regions. However, the application of proteomics data to genome annotation is hindered by the lack of suitable tools and methods to achieve automatic data processing and genome mapping at high accuracy and throughput.
Item Type: | Book Section / Chapter |
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Uncontrolled Keywords: | Computational genomics; Computational proteomics; Functional genomics; Genome; Genome annotation; MS; Proteomics |
Divisions: | Sabancı University Nanotechnology Research and Application Center |
Depositing User: | Shiv Kumar Bharadwaj |
Date Deposited: | 30 Jul 2023 22:34 |
Last Modified: | 30 Jul 2023 22:34 |
URI: | https://research.sabanciuniv.edu/id/eprint/46582 |