doi.bio/frank_j_poelwijk

Frank J. Poelwijk

Overview

Frank J. Poelwijk is a researcher in the field of biochemistry and genomics, with a focus on machine learning and AI techniques. He currently works at the Dana-Farber Cancer Institute in Boston, USA, and has previously held positions at the University of Texas Southwestern Medical Center and the University of Amsterdam. Poelwijk's research interests include evolutionary biology, protein structure and function, and the application of machine learning to biological systems.

Education and Career

Poelwijk obtained his PhD from the University of Amsterdam, where he worked on understanding the context-dependence of mutations and the significance of epistasis in biological systems. After completing his PhD, he joined the University of Texas Southwestern Medical Center as a postdoctoral researcher. In 2016, he moved to the Dana-Farber Cancer Institute, where he continues to work as a researcher.

Research Contributions and Publications

Poelwijk has made significant contributions to the field of evolutionary biology, particularly in understanding the role of epistasis in protein evolution. He has published several articles in prestigious journals such as PLoS Comput. Biol. and Nature Communications. Some of his notable works include:

• The Context-Dependence of Mutations: A Linkage of Formalisms (2016): In this article, Poelwijk and his colleagues propose a framework for understanding the context-dependence of mutations by linking different formalisms. They introduce the concept of "epistasis", which refers to the non-independence of mutation effects, and explore its implications for relating genotype to phenotype.
• Learning the pattern of epistasis linking genotype and phenotype in a protein (2019): In this Nature Communications article, Poelwijk and his team investigate the pattern of epistasis, which is critical for understanding protein evolution. They conduct a comprehensive experimental study on 213 mutants of a fluorescent protein and discover a large number of high-order epistatic interactions. They also demonstrate the sparsity of epistasis, which enables novel computational strategies for predicting phenotypes.
• Optimality and evolution of transcriptionally regulated gene expression (2011): Poelwijk and colleagues explore the evolution of transcriptionally regulated gene expression. They find that gene regulation systems evolve towards optimal regulatory responses when challenged with variable environments.
• Evolutionary Potential of a Duplicated Repressor-Operator Pair: Simulating Pathways Using Mutation Data (2006): In this PLoS Comput. Biol. article, Poelwijk and co-authors use simulation techniques to study the evolutionary potential of a duplicated repressor-operator pair. They demonstrate the importance of duplication events and the subsequent divergence process in evolutionary biology.

Awards and Recognition

Poelwijk's research has been recognised by various organisations, and he has received several awards for his contributions to the field. He was also listed as a co-inventor on multiple patent applications related to his research.

Frank J. Poelwijk

Overview

Frank J. Poelwijk is a researcher in the fields of machine learning, biochemistry, and genomics. He currently works as a scientist/engineer at Generate Biomedicines, a company pioneering the field of generative biology for drug development.

Education and Career

Poelwijk previously held positions at the Dana-Farber Cancer Institute, University of Texas Southwestern Medical Center, and the Green Center for Systems Biology. He has also been affiliated with the University of Twente and Wageningen University & Research.

Research and Publications

Poelwijk's research interests include evolutionary biology, protein structure and function, gene regulation, and the application of machine learning in these areas. His notable publications include:

• "The Context-Dependence of Mutations: A Linkage of Formalisms" (2016)
• "Optimality and evolution of transcriptionally regulated gene expression" (2011)
• "Evolutionary Potential of a Duplicated Repressor-Operator Pair: Simulating Pathways Using Mutation Data" (2006)
• "Illuminating protein space with a programmable generative model" (published in Nature)

Awards and Recognition

Poelwijk's work has been recognised by CNBC, and Generate Biomedicines was listed as one of the top 100 private deep tech companies in the world by XPRIZE Bessemer Venture Partners in 2023.

Youtube Videos

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Still

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Youtube Title: Chiccoman Ravanne Tambour Random x Frank J Refix 2017

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Chiccoman Ravanne Tambour Random x Frank J Refix 2017

Youtube Title: Obsesion (No Es Amor) (Spanish Version)

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Frankie J - More Than Words (Video - English)

Youtube Title: Still - Frankie J

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Still - Frankie J

Youtube Title: Frank J - Ey Tamam Sa (Audio 2021)

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Frank J - Ey Tamam Sa (Audio 2021)