Cited by 90Machine Learning in BioinformaticsProtein purification and stabilityProtein Structure and Dynamics

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Prediction of protein solubility in Escherichia coli using logistic regression

Diaz, Armando A., Tomba, Emanuele, Lennarson, Reese, Richard, Rex, Bagajewicz, Miguel J., Harrison, Roger G.·2010·Biotechnology and Bioengineering

DOI 10.1002/bit.22537

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Abstract

In this article we present a new and more accurate model for the prediction of the solubility of proteins overexpressed in the bacterium Escherichia coli . The model uses the statistical technique of logistic regression. To build this model, 32 parameters that could potentially correlate well with solubility were used. In addition, the protein database was expanded compared to those used previously. We tested several different implementations of logistic regression with varied results. The best implementation, which is the one we report, exhibits excellent overall prediction accuracies: 94% for the model and 87% by cross‐validation. For comparison, we also tested discriminant analysis using the same parameters, and we obtained a less accurate prediction (69% cross‐validation accuracy for the stepwise forward plus interactions model). Biotechnol. Bioeng. 2010; 105: 374–383. © 2009 Wiley Periodicals, Inc.

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Authors: Diaz, A. A., Tomba, E., Lennarson, R., Richard, R., Bagajewicz, M. J., & Harrison, R. G.
Affiliations: University of Oklahoma (US)
Corresponding author: Harrison, Roger G.
ORCID: Bagajewicz, Miguel J.
Harrison, Roger G.
Venue: Biotechnology and Bioengineering
Publisher: Wiley
Published: 2009-10-20
Volume: 105
Issue: 2
Pages: 374-383
ISSN: 0006-3592 (ISSN-L)
1097-0290
DOI: 10.1002/bit.22537
OpenAlex: W2116818641
Cited by: 90
References: 37
Citations by year: 2026: 2 · 2025: 6 · 2024: 6 · 2023: 6 · 2022: 6 · 2021: 5 · 2020: 6 · 2019: 9 · 2018: 11 · 2017: 7 · 2016: 6 · 2015: 4 · 2014: 10 · 2013: 3 · 2012: 2
FWCI: 0.40
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Biotechnology and Bioengineering (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords: protein solubility prediction, Escherichia coli, recombinant protein overexpression, logistic regression, discriminant analysis, solubility parameter, protein databases, cross-validation accuracy
MeSH terms: Inclusion Bodies, Escherichia coli, Recombinant Proteins, Solubility, Logistic Models, Databases, Protein

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Prediction of protein solubility in Escherichia coli using logistic regression

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