Searching across hundreds of databases

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

Resource Name
RRID:SCR_007990 RRID Copied      
PDF Report How to cite
GENIA Project: Mining literature for knowledge in molecular biology (RRID:SCR_007990)
Copy Citation Copied
Resource Information

URL: http://www.nactem.ac.uk/genia/

Proper Citation: GENIA Project: Mining literature for knowledge in molecular biology (RRID:SCR_007990)

Description: Resources and tools from a project to automatically extract useful information from texts written by scientists to help overcome the problems caused by information overload. The primary annotated resource created is the GENIA corpus, a collection of biomedical literature which consists of multiple layers of annotation, encompassing both syntactic and semantic annotation. The project also created or coordinated the annotation of multiple other corpus resources. Additionally, a rich set of automatic tools are available for various annotation tasks, most trained on various parts of the GENIA corpus annotations. The GENIA corpus was developed to provide a reference material for the development of bio-TM systems. The corpus currently contains 1,999 Medline abstracts which were collected using the three MeSH terms, human, blood cells, and transcription factors. The corpus has been annotated with various levels of linguistic and semantic information. The GENIA corpus includes the following: * POS annotation * Treebank * Coreference Annotation * Term annotation * Event annotation * Relation annotation * Cellular localization * Disease-Gene association * Pathway corpus The GENIA Project initiated the BioNLP Shared Task series and has organized a number of tasks in three different shared task events, many using resources based on GENIA Corpus annotations. Tools include: * XConc suite: a collection of XML-based tools which are integrated to support the corpus development and annotation.

Abbreviations: GENIA

Resource Type: software resource

Keywords: annotation, biomedical, computational linguistics, text mining, literature, molecular biology, syntactic annotation, semantic annotation, syntax, semantics, information extraction, blood cell, transcription factor, protein interaction, task

Expand All
This resource

is listed by

FORCE11

is related to

MEDLINE

has parent organization

National Centre for Text Mining

has parent organization

University of Tokyo; Tokyo; Japan

Usage and Citation Metrics

We found {{ ctrl2.mentions.total_count }} mentions in open access literature.

We have not found any literature mentions for this resource.

We are searching literature mentions for this resource.

Most recent articles:

{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})

Checkfor all resource mentions.

Collaborator Network

A list of researchers who have used the resource and an author search tool

Find mentions based on location


{{ ctrl2.mentions.errors.location }}

A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.

Ratings and Alerts

No rating or validation information has been found for GENIA Project: Mining literature for knowledge in molecular biology.

No alerts have been found for GENIA Project: Mining literature for knowledge in molecular biology.

Data and Source Information