Machine learning-based analysis of the impact of 5′ untranslated region on protein expression Article Swipe
Linfeng Wang
,
Sujia Liu
,
Jia-Xin Huang
,
Haifeng Zhu
,
Shuyu Li
,
Yannan Li
,
Sen Chen
,
Jianying Han
,
Yin Zhu
,
Jiahao Wu
,
Wentao Liao
,
Hongmei Zhang
,
Haiyan Zeng
,
Shaoting Li
,
Shu‐Ping Zhao
,
Bingwei Wang
,
Jiaqi Lin
,
Ji Zeng
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkaf861
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkaf861
The 5′ untranslated region (5′UTR) plays a crucial regulatory role in messenger RNA (mRNA), with modified 5′UTRs extensively utilized in vaccine production, gene therapy, etc. Nevertheless, manually optimizing 5′UTRs may encounter difficulties in balancing the effects of various cis-elements. Consequently, multiple 5′UTR libraries have been created, and machine learning models have been employed to analyze and predict translation efficiency (TE) and protein expression, providing insights into critical regulatory features. On the one hand, these screening libraries, based on TE and mean ribosome load, struggle to accurately quantify protein expression; on the other hand, a precise method for quantifying 5′UTRs necessitates a significantly costlier library. To resolve this dilemma, we constructed a library utilizing firefly luciferase as the reporter to measure accurate protein expression. In addition, we optimized the library construction method by clustering mRNA sequences to reduce redundant data and minimize the size of the dataset. This dual strategy by increasing accuracy and reducing dataset size was found to be effective in predicting the 5′UTRs from the PC3 cell line.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/nar/gkaf861
- OA Status
- gold
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4414082375
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https://openalex.org/W4414082375Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/nar/gkaf861Digital Object Identifier
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Machine learning-based analysis of the impact of 5′ untranslated region on protein expressionWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
- Publication date
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2025-08-16Full publication date if available
- Authors
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Linfeng Wang, Sujia Liu, Jia-Xin Huang, Haifeng Zhu, Shuyu Li, Yannan Li, Sen Chen, Jianying Han, Yin Zhu, Jiahao Wu, Wentao Liao, Hongmei Zhang, Haiyan Zeng, Shaoting Li, Shu‐Ping Zhao, Bingwei Wang, Jiaqi Lin, Ji ZengList of authors in order
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https://doi.org/10.1093/nar/gkaf861Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.1093/nar/gkaf861Direct OA link when available
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0Total citation count in OpenAlex
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41Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.various | 38 |
| abstract_inverted_index.5′UTRs | 17, 29, 99, 165 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.accuracy | 152 |
| abstract_inverted_index.accurate | 121 |
| abstract_inverted_index.costlier | 103 |
| abstract_inverted_index.created, | 46 |
| abstract_inverted_index.critical | 67 |
| abstract_inverted_index.dataset. | 146 |
| abstract_inverted_index.dilemma, | 108 |
| abstract_inverted_index.employed | 53 |
| abstract_inverted_index.insights | 65 |
| abstract_inverted_index.learning | 49 |
| abstract_inverted_index.library. | 104 |
| abstract_inverted_index.manually | 27 |
| abstract_inverted_index.minimize | 141 |
| abstract_inverted_index.modified | 16 |
| abstract_inverted_index.multiple | 41 |
| abstract_inverted_index.quantify | 87 |
| abstract_inverted_index.reducing | 154 |
| abstract_inverted_index.reporter | 118 |
| abstract_inverted_index.ribosome | 82 |
| abstract_inverted_index.strategy | 149 |
| abstract_inverted_index.struggle | 84 |
| abstract_inverted_index.therapy, | 24 |
| abstract_inverted_index.utilized | 19 |
| abstract_inverted_index.(5′UTR) | 5 |
| abstract_inverted_index.addition, | 125 |
| abstract_inverted_index.balancing | 34 |
| abstract_inverted_index.effective | 161 |
| abstract_inverted_index.encounter | 31 |
| abstract_inverted_index.features. | 69 |
| abstract_inverted_index.libraries | 43 |
| abstract_inverted_index.messenger | 12 |
| abstract_inverted_index.optimized | 127 |
| abstract_inverted_index.providing | 64 |
| abstract_inverted_index.redundant | 138 |
| abstract_inverted_index.screening | 75 |
| abstract_inverted_index.sequences | 135 |
| abstract_inverted_index.utilizing | 113 |
| abstract_inverted_index.accurately | 86 |
| abstract_inverted_index.clustering | 133 |
| abstract_inverted_index.efficiency | 59 |
| abstract_inverted_index.increasing | 151 |
| abstract_inverted_index.libraries, | 76 |
| abstract_inverted_index.luciferase | 115 |
| abstract_inverted_index.optimizing | 28 |
| abstract_inverted_index.predicting | 163 |
| abstract_inverted_index.regulatory | 9, 68 |
| abstract_inverted_index.constructed | 110 |
| abstract_inverted_index.expression, | 63 |
| abstract_inverted_index.expression. | 123 |
| abstract_inverted_index.expression; | 89 |
| abstract_inverted_index.extensively | 18 |
| abstract_inverted_index.production, | 22 |
| abstract_inverted_index.quantifying | 98 |
| abstract_inverted_index.translation | 58 |
| abstract_inverted_index.construction | 130 |
| abstract_inverted_index.difficulties | 32 |
| abstract_inverted_index.necessitates | 100 |
| abstract_inverted_index.untranslated | 3 |
| abstract_inverted_index.Consequently, | 40 |
| abstract_inverted_index.Nevertheless, | 26 |
| abstract_inverted_index.cis-elements. | 39 |
| abstract_inverted_index.significantly | 102 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 18 |
| citation_normalized_percentile.value | 0.39387258 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |