| Autor: |
Sarah Ali, Ahmed M. Mehdi, Ali Naqi, Mashal Fatima, Musarat Ishaq, Rubbiya A. Ali |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Encyclopedia of Bioinformatics and Computational Biology (3) |
| DOI: |
10.1016/b978-0-12-809633-8.20466-4 |
| Popis: |
The abundance of proteins in a cell governs the function they can play in controlling cellular environment. Determining the abundance of protein using experimental methods is very important, however the predicted protein abundance can reduce the experimental cost and can help us in understanding the cellular environment and translational efficiency. Diverse and large-scale mRNA expression and proteomics data sets are available that could link transcriptional process with protein translation and offer new opportunities to build mathematical models of predicting protein abundance. We review the determinants of protein abundance, focusing on the statistical and probabilistic approaches as well as the experimental methods. We present a case study on how to collect experimental data and use available methods of protein abundance. Our case study uses two linear and two probabilistic models that predict protein abundance. Available prediction methods are solely trained on either S. cerevisiae or S. pombe, we also review how best these methods can be used for other species. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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