Search Results for "text mining concept"

Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature.

GNAT is a BioNLP/text mining tool to recognize and identify gene/protein names in natural language text. It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline.

Framework for text mining, data integration and data analysis. Keywords: ontology and graph alignment, relation mining, warehouse, semantic database integration, bioinformatics, systems biology, microarray, Java.

A text mining system for extraction of protein-protein interactions from biomedical text.

Contextor is a light-weight simple-to-use Java based library to help developers and researchers working with the general concept of a resource; as examples, resources can be text resources, web resources, images and videos.

PubCurator is a biomedical text mining platform and validation helper built on top of Eclipse RCP.

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.

OpenDMAP (Open Source Direct Memory Access Parser) is a natural language processing (text mining) application: a semantic parser for information extraction.

LAITOR is a text mining software developed to find co-occurrence of biological entities (gene/protein terms) together with biointeractions and concepts term from customized dictionaries.

@Note2 is now available in www.anote-project.org @Note is a Biomedical Text Mining workbench that integrates current Biomedical Text Mining (BioTM) methods and provides biologists with intuitive tools capable of supporting their bibliographic searches and further literature curation.

GraphSpider is a pattern matcher which searches parsed text in phrase-structure tree or dependency graph format for syntactic structures matching a set of patterns in MPL, a regexp-like pattern language. Applications: information extraction, text mining.