This is a database for feature representation of ESM2, which includes Swiss data, Swiss normalized data, original TrEMBL data, original TrEMBL normalized data, non-homology TrEMBL data and Table S10.N
The representation learning models constructed in this research is used to describe the five biological features of proteins. These vectors together constitute the protein deep profile matrix.
Appendix 1. List of primers sets used for amplification of sequences from yeast genomic DNA and further Gibson assembly of overexpression plasmids. Appendix 2. MS data set of identified proteins. App