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:
In [3]: from NERO.corpus import corpus
# Directly access basic dataframe attributes
In [4]: corpus.columns
In [5]: corpus.shape
# access to the whole dataframe
In [6]: corpus._data
# Having directly access to columns by calling them as an attribute
In [7]: corpus.semantic_class_actionType
In [8]:
# Using documentation
In [8]: corpus.procset_topic_bd.__doc__
# other generic and multipurpose functions
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-0.0.8.tar.gz
(6.4 MB
view details)
Built Distribution
File details
Details for the file NERO-nlp-0.0.8.tar.gz
.
File metadata
- Download URL: NERO-nlp-0.0.8.tar.gz
- Upload date:
- Size: 6.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.0 CPython/3.8.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9c802cb0aca99921027fe757735337eb84eeb5d77f3a417362a9d266ee9cddef |
|
MD5 | 4ce2d4ebd90c8d5c8256e0321fe4f963 |
|
BLAKE2b-256 | 900afef7c4fe0749f57b4fe175e14762bd8a382f8cad6be3c531fe4798a5f2cc |
File details
Details for the file NERO_nlp-0.0.8-py3-none-any.whl
.
File metadata
- Download URL: NERO_nlp-0.0.8-py3-none-any.whl
- Upload date:
- Size: 6.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.0 CPython/3.8.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f19d87036b2a720388754d11d26bc421c3bc842e18bf7e8cfee4d30c03afc2a8 |
|
MD5 | 0450dccf3547f41262d674d217396d52 |
|
BLAKE2b-256 | c9c50f9bf0e79969798ff1ec00043fe215d7e09f884be43020f363d2fbec1ad2 |