Filip Buric

发表

Learning the Regulatory Code of Gene Expression

A. Zelezniak, Jan Zrimec, Filip Buric, 2021, Frontiers in Molecular Biosciences.

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

V. Verendel, V. Siewers, A. Zelezniak, 2020, Nature communications.

Pattern formation and chemical evolution in extended Gray-Scott models

Filip Buric, 2014 .

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

V. Verendel, V. Siewers, Jan Zrimec, 2019, Nature Communications.

Learning deep representations of enzyme thermal adaptation

Gang Li, Jan Zrimec, M. Engqvist, 2022, bioRxiv.

Mapping the proteome with data-driven methods: A cycle of measurement, modeling, hypothesis generation, and engineering

Filip Buric, 2021 .

Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra

Aleksej Zelezniak, Jan Zrimec, Filip Buric, 2020, bioRxiv.

Parallel factor analysis enables quantification and identification of highly-convolved data independent-acquired protein spectra

Aleksej Zelezniak, Jan Zrimec, Filip Buric, 2020, bioRxiv.

The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost

Jan Zrimec, Filip Buric, Xiaozhi Fu, 2023, bioRxiv.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Jan Zrimec, Filip Buric, M. Mülleder, 2024, Protein science : a publication of the Protein Society.