netam 0.2.0

Neural network models for antibody affinity maturation

netam

Neural NETworks for antibody Affinity Maturation.

pip installation

Netam is available on PyPI, and works with Python 3.8 through 3.11.

pip install netam

This will allow you to use the models.

However, if you wish to interact with the models on a more detailed level, you will want to do a developer installation (see below).

Pretrained models

Pretrained models will be downloaded on demand, so you will not need to install them separately.

The models are named according to the following convention:

ModeltypeSpeciesVXX-YY

where:

• Modeltype is the type of model, such as Thrifty for the "thrifty" SHM model
• Species is the species, such as Hum for human
• XX is the version of the model
• YY is any model-specific information, such as the number of parameters

If you need to clear out the cache of pretrained models, you can use the command-line call:

netam clear_model_cache

Usage

See the examples in the notebooks directory.

Developer installation

From a clone of this repository, install using:

python3.11 -m venv .venv
source .venv/bin/activate
make install

Note that you should be fine with an earlier version of Python. We target Python 3.9, but 3.11 is faster.

Experiments

If you are running one of the experiment repos, such as:

• thrifty-experiments-1
• dnsm-experiments-1

you will want to visit those repos and follow the installation instructions there.