Article

Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies

2019-05-02

Abstract excerpt

<h4> A bstract </h4> Improved understanding of properties that mediate protein solubility and resistance to aggregation are important for developing biopharmaceuticals, and more generally in biotechnology and synthetic biology. Recent acquisition of large datasets for antibody biophysical properties enables the search for predictive models. In this report, machine learning methods are used to derive models for...

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Literature Corpus work: 4e45d09f-afac-57a7-ada8-bc16fc608877
DOI: 10.1101/625830

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