A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli

Pattern recognition in bioinformatics

(2013) D. de Ridder et al.   BRIEFINGS IN BIOINFORMATICS

Discrimination of soluble and aggregation-prone proteins based on sequence information

(2013) Yaping Fang et al.   Molecular BioSystems

ESPRESSO: A system for estimating protein expression and solubility in protein expression systems

(2013) Shuichi Hirose et al.   PROTEOMICS

PROSO II - a new method for protein solubility prediction

(2012) Pawel Smialowski et al.   FEBS Journal

Comprehensive Decision Tree Models in Bioinformatics

(2012) Gregor Stiglic et al.   PLoS One

Exploring Sequence Characteristics Related to High-Level Production of Secreted Proteins in Aspergillus niger

(2012) Bastiaan A. van den Berg et al.   PLoS One

Statistical analysis of features associated with protein expression/solubility in an in vivo Escherichia coli expression system and a wheat germ cell-free expression system

(2011) Shuichi Hirose et al.   JOURNAL OF BIOCHEMISTRY

SOLpro: accurate sequence-based prediction of protein solubility

(2009) Christophe N. Magnan et al.   BIOINFORMATICS

Prediction of protein solubility inEscherichia coliusing logistic regression

(2009) Armando A. Diaz et al.   BIOTECHNOLOGY AND BIOENGINEERING

Bimodal protein solubility distribution revealed by an aggregation analysis of the entire ensemble of Escherichia coli proteins

(2009) T. Niwa et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA