In silico analysis of hypothetical proteins in Pseudomonas aeruginosa PAC1: Structural and functional insights

This study demonstrates a systematic computational approach for characterizing hypothetical proteins in bacterial genomes. WP_003099663.1 and WP_010793930.1 exhibit promising structural and functional features and warrant further experimental investigation.

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Publication Details

Journal
Journal of Genetic Engineering and Biotechnology
Published
2025-06-19
DOI
https://doi.org/10.1016/j.jgeb.2025.100515
Citations
1
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
0.81
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article

In silico analysis of hypothetical proteins in Pseudomonas aeruginosa PAC1: Structural and functional insights

Yousra Tagelsir Ahmed, Mutaz Mohammed Abdallah, Mawada Yahia, Ruaa Abdalla Ibrahim Suliman
1 citations
Journal of Genetic Engineering and Biotechnology
Machine Learning in Bioinformatics
0.81
article

In silico analysis of hypothetical proteins in Pseudomonas aeruginosa PAC1: Structural and functional insights

Yousra Tagelsir Ahmed, Mutaz Mohammed Abdallah, Mawada Yahia, Ruaa Abdalla Ibrahim Suliman
article en
1 citations

Abstract

This study demonstrates a systematic computational approach for characterizing hypothetical proteins in bacterial genomes. WP_003099663.1 and WP_010793930.1 exhibit promising structural and functional features and warrant further experimental investigation.

Journal of Genetic Engineering and BiotechnologyVol. 23(3)
Alzaiem Alazhari University (SD), Mohamed I University (MA), Northeast Forestry University (CN)
Openalex Percentile: Top 27%
Machine Learning in Bioinformatics
0.81
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