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Data is hierarchically clustered on the server side using the Python library SciPy with default parameters: cosine distance metric and average linkage type.
DNNs were implemented using the Python library Tensorflow [35].
We solve the constraint equations and perform all numerics using the Python library SciPy [32].
All network properties were computed using the Python library NetworkX version 1.2 [ 47].
Using the Python library DendroPy (Sukumaran and Holder 2010), we calculated the patristic distance matrix for each neighbor-joining tree.
The consensus of most parsimonious proteome trees was obtained using the Python library SumTrees with the option of 50% majority-rule [ 87].
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checking if python include files and libraries work... configure: error: could not run a test that used the python library.
The scripts of the benchmarking platform are written in Python and use the Python library of the RDKit [42].
We used the Python libraries PyQt4, spyderlib and guiqwt to build the workbench and graphical explorers and used numpy and scipy for the numerical data structures and algorithms.
Here we are using the python nltk library to do term frequency-inverse document frequency natural language processing on every article in the corpus.
BACKGROUND: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com