Tmpri2-005.7z

These files typically contain curated sequences of proteins that cross cell membranes, used to distinguish between transmembrane helices, signal peptides, and globular domains.

Authors: Jeppe Hallgren, Konstantinos D. Tsirigos, et al. Journal: Nature Communications (2022).

The "TmPri" (Transmembrane Primary) naming convention is standard for the benchmark sets used to develop , a leading deep learning tool for protein structure prediction. TmPri2-005.7z

The repository for DeepTMHMM contains the scripts and links to the underlying datasets used in the Nature Communications paper.

If you are looking for the contents of this specific archive for replication or research, they are usually hosted on: These files typically contain curated sequences of proteins

Read on Nature Communications | Source Code & Data on GitHub Context of the File

The primary research group's resource page . Journal: Nature Communications (2022)

This dataset is primarily used in bioinformatics for training and evaluating machine learning models related to . Associated Research Paper The core research paper associated with this dataset is: