Quick View on Bacterial translation analysis web tools
Abstract
Bacterial translation was learnt by researcher from the past four decades and significant data was generated. Inquisite to understand performance of the bacteria to produce a particular recombinant protein so as to pre-evaluate and make necessary modifications for optimal production is the key interest for researcher and biopharma manufacturers. Over a decade various databases were built and based on this valuable data webtools were developed which enable researcher to tweak the strategy beforehand. Here in this article we outlined various database and webtools based on protein translation which are currently being used.
Keywords:
Bacterial translation, webtools, biopharma manufacturers
References
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2. Kumari R, Michel AM, Baranov PV. PausePred and Rfeet: webtools for inferring ribosome pauses and visualizing footprint density from ribosome profiling data. RNA (New York, NY). 2018;24(10):1297-304.
3. Liu Q, Shvarts T, Sliz P, Gregory RIJNar. RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution. 2020;48(W1):W218-W29.
4. Xie M, Yang L, Chen G, Wang Y, Xie Z, Wang HJBiB. RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data. 2022;23(2):bbab559.
5. Tjeldnes H, Labun K, Torres Cleuren Y, Chyżyńska K, Świrski M, Valen EJBb. ORFik: a comprehensive R toolkit for the analysis of translation. 2021;22(1):1-16.
6. Bhandari BK, Lim CS, Gardner PPJNAR. TISIGNER. com: web services for improving recombinant protein production. 2021;49(W1):W654-W61.
7. 7. Bhandari BK. Computational tools for improving recombinant protein production: University of Otago; 2021.
8. Stansfield I, Romano MCJapa. ExpressInHost: A codon tuning tool for the expression of recombinant proteins in host microorganisms. 2021.
9. de Toro M, Lanza VF, Vielva L, Redondo-Salvo S, de la Cruz F. Plasmid reconstruction from Next-Gen data: a detailed protocol for the use of PLACNETw for the reconstruction of plasmids from WGS datasets. Horizontal Gene Transfer: Springer; 2020. p. 323-39.
10. Packiam KAR, Ooi CW, Li F, Mei S, Tey BT, Ong HF, et al. PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli. 2022.
11. Salis HM. The ribosome binding site calculator. Methods in enzymology. 2011;498:19-42.
12. Zhao L, Abedpour N, Blum C, Kolkhof P, Beller M, Kollmann M, et al., editors. Predicting gene expression level in E. coli from mRNA sequence information. 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB); 2019: IEEE.
13. LaFleur TL, Hossain A, Salis HMJNc. Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. 2022;13(1):1-15.
Published
03/08/2023
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How to Cite
Kona, V. S. K., Kanigiri, D. S., Azharuddin, M., & Arrolla, L. (2023). Quick View on Bacterial translation analysis web tools. The Journal of Multidisciplinary Research, 3(2), 14-19. https://doi.org/10.37022/tjmdr.v3i2.468
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