Can protein expression be ‘solved’?Baranowski, Catherine (Avtor) Garcia Martin, Hector (Avtor) Oyarzún, Diego A. (Avtor) Spinner, Aviv (Avtor) Desai, Bijoy (Avtor) Petzold, Christopher J. (Avtor) Nikolados, Evangelos-Marios (Avtor) Jaaks-Kraatz, Sebastian (Avtor) Gaber, Aljaž (Avtor) Chalkley, Robert J. (Avtor) Scannell, Devin (Avtor) Sevey, Rachel (Avtor) Jewett, Michael C. (Avtor) Kelly, Peter J. (Avtor) DeBenedictis, Erika A. (Avtor) protein expressionmachine learningpredictive modelsopen datasetsHeterologous protein expression is a fundamental technique used frequently in modern day biology. It enables scientific exploration of protein function as well as development of lifesaving medicines and economically impactful industrial products. Protein expression experiments primarily remain an experience-guided trial and error situation, even though it is an approach used by nearly all biologists. Generating an openly available, large-scale protein expression dataset that spans organisms and uses a standard experimental approach would provide the machine learning community with a foundation for building a multispecies predictive model of expression. A predictive model of protein expression would have a profound commercial impact and could replace countless hours of experimentation with a higher-probability directed approach.20252025-06-09 09:20:59Članek v reviji169760sl