TooT-BERT-T

TooT-BERT-T is a tool that predicts transmembrane transporter proteins using ProtBERT-BFD and logistic regression. This tool takes protein sequences in fasta format as input and outputs the predicted labels for sequence ID - transporter, nontransporter.

The method used in this tool is described in the paper "TooT-BERT-T: A BERT Approach on Discriminating Transport Proteins from Non-transport Proteins" by H. Ghazikhani and G. Butler, published in the proceedings of the 16th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2022).

Installation

The list of required python packages is included in the file "requirements.txt". To install these packages, run the following command:

pip install -r requirements.txt

Usage

You can run the program as follows:

python run.py [input_fasta_file] [output_file]

For example:

python run.py test.fasta out.txt

where "test.fasta" is the input file containing protein sequences in fasta format and "out.txt" is the output file where the predicted labels will be written.

Note: This tool runs faster on a GPU.