A biomedical Named Entity (Recognition) Ontology
Project description
NERO is a biomedical Named Entity (Recognition) Ontology.
Using NERO, we annotated a large biomedical corpus to enable a broad spectrum of natural language processing and biomedical machine learning tasks.
NERO-nlp is a wrapper around this corpus.
Sample usage:
# access basic dataframe attributes directly
In [4]: corpus.columns
In [5]: corpus.shape
# access to the whole dataframe
In [6]: corpus._data
# Having directly access to columns by calling then as an attribute
In [7]: corpus.semantic_class_actionType
In [8]:
# Using documentation in order to gain more insight into
# functionality of the attribute.
In [8]: corpus.procset_topic_bd.__doc__
# other generic and multipurpose functionalions
In [9]: corpus.procset_topic_bd('aut')
In [10]: corpus.plot_protein_domain_entity()
Installation:
For running the NERO-nlp you need to have python3.7+ and pandas installed. For installation you can use pip
or pip3
for installation.
# Install
sudo pip3 install NERO-nlp
# or
sudo python3 -m pip install NERO-nlp
# Upgrade
sudo pip3 install NERO-nlp --upgrade
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
NERO-nlp-0.0.3.tar.gz
(3.3 kB
view hashes)