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Št. zadetkov: 2
Learning deep representations of enzyme thermal adaptation
Gang Li, Filip Buric, Jan Zrimec, Sandra Viknander, Jens Nielsen, Aleksej Zelezniak, Martin K. M. Engqvist
Izvirni znanstveni članek
Oznake: bioinformatika;optimalna temperatura rasti;termostabilnost proteinov;globoko ucenje;bioinformatics;deep neural networks;enzyme catalytic temperatures;optimal growth temperatures;protein thermostability;transfer learning;
Temperature is a fundamental environmental factor that shapes the evolution of organisms. Learning thermal determinants of protein sequences in evolution thus has profound significance for basic biology, drug discovery, and protein engineering. Here, we use a data set of over 3 million BRENDA enzyme ...
Leto: 2022 Vir: Nacionalni inštitut za biologijo (NIB)
Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost
Filip Buric, Sandra Viknander, Xiaozhi Fu, Oliver Lemke, Oriol Gracia Carmona, Jan Zrimec, Lukasz Szyrwiel, Michael Mülleder, Markus Ralser, Aleksej Zelezniak
Izvirni znanstveni članek
Oznake: molekularna biologija;biotehnologija;bioinformatika;globoko učenje;izražanje genov;sintetična biologija;obilje beljakovin;aminokislinsko zaporedje;evolucijska selekcija;molecular biology;biotechnology;bioinformatics;deep learning;gene expression;synthetic biology;protein abundance;amino acid sequence;evolutionary selection;transformer model;MGEM (Mutation guided by an embedded manifold);
Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, th ...
Leto: 2025 Vir: Nacionalni inštitut za biologijo (NIB)
Št. zadetkov: 2
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