Skip to main content

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-0.0.5.tar.gz (3.3 kB view details)

Uploaded Source

Built Distribution

NERO_nlp-0.0.5-py3-none-any.whl (3.6 kB view details)

Uploaded Python 3

File details

Details for the file NERO-nlp-0.0.5.tar.gz.

File metadata

  • Download URL: NERO-nlp-0.0.5.tar.gz
  • Upload date:
  • Size: 3.3 kB
  • 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

Hashes for NERO-nlp-0.0.5.tar.gz
Algorithm Hash digest
SHA256 08f3876651bf06d18de562468a70f19e5d16fd8bba3d19bff86a2edaf08f91f6
MD5 0c5b85c9cdbccfaff9388de87c456097
BLAKE2b-256 f688eea1c191dc41b39c880deddc485c62cb8ab113a1e726502ac08aa2b8873b

See more details on using hashes here.

File details

Details for the file NERO_nlp-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: NERO_nlp-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 3.6 kB
  • 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

Hashes for NERO_nlp-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 7b9a0a6a059946ad6c31767797689b4310486169475620808a4659c326ffbf12
MD5 45dba5e936d5f8fb646ff40e778f9db4
BLAKE2b-256 34587c9bc6f83f12e8e016a7ca95705393c5161d527aa8b838611faf4e530b69

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page