Pard

Stable version with Pairwise Distance, Sneath, Miyata, Epstein, Grantham distances, Experimental exchangeability score, conformational similarity weight matrix (Kolaskar), EMPAR (Exchange Matrix derived from PARameters) score and 7 Koshi-Goldstein likelihood score computations supported. 3 letter code as well as 1 letter code are supported. Please install pard with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.

Stable version with Pairwise Distance, Sneath, Miyata, Epstein, Grantham distances, Experimental exchangeability score, conformational similarity weight matrix (Kolaskar), EMPAR (Exchange Matrix derived from PARameters) score and 7 Koshi-Goldstein likelihood score computations supported. 3 letter code as well as 1 letter code are supported. Please install pard with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.

Stable version with Sneath, Miyata, Epstein, Grantham distances, Experimental exchangeability score, conformational similarity weight matrix (Kolaskar), and 7 Koshi-Goldstein likelihood score computations supported. 3 letter code as well as 1 letter code are supported. Please install pard with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.

Stable version with Sneath, Miyata, Epstein, Grantham distances, Experimental exchangeability score computations supported, and 7 Koshi-Goldstein likelihood score computations supported. 3 letter code as well as 1 letter code are supported. Please install pard with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.

Stable version with _Sneath_, _Miyata_, _Epstein_, _Grantham_ distances, _Experimental exchangeability_ score computations supported, and 3 Koshi-Goldstein likelihood score computations supported. 3 letter code as well as 1 letter code are supported. Please install `pard` with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.

Stable version with _Sneath_, _Miyata_, _Epstein_, _Grantham_ distances and _Experimental exchangeability_ score computations supported. 3 letter code as well as 1 letter code are supported. Please install `pard` with PyPI (cf. documentation on [GitHub](https://github.com/MICS-Lab/pard) or [PyPI](https://pypi.org/project/pard/)). Downloading source files from zenodo is not ideal.