BioAnnote 2.0.0 – Annotate Biomedical Texts by using different high-quality online Resources

BioAnnote 2.0.0

:: DESCRIPTION

BioAnnote is a desktop application is able to annotate biomedical texts by using different high-quality online resources, such as Medlineplus and Freebase.

::DEVELOPER

SING Group.

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
java

:: DOWNLOAD

BioAnnote

:: MORE INFORMATION

Citation

Comput Methods Programs Biomed. 2013 Jul;111(1):139-47. doi: 10.1016/j.cmpb.2013.03.007.
BioAnnote: a software platform for annotating biomedical documents with application in medical learning environments.
López-Fernández H, Reboiro-Jato M, Glez-Peña D, Aparicio F, Gachet D, Buenaga M, Fdez-Riverola F.

BioClass – tool for Biomedical Text Classification

BioClass

:: DESCRIPTION

BioClass is a tool for biomedical text classification. Through it, a researcher can split a document set, directly related with a specific topic, into relevant or irrelevant documents. BioClass also supports several algorithms in order to increase the classification process efficiency and provides a set of powerful interfaces to analyse, filter and compare obtained results. In addition, all the operations than can be performed in BioClass are connected between them, so that the classification process is completely guided.

::DEVELOPER

SING Group.

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows
java

:: DOWNLOAD

BioClass

:: MORE INFORMATION

@Note2 2.5.0 – Biomedical Text Mining platform

@Note2 2.5.0

:: DESCRIPTION

@Note is Biomedical Text Mining platform that copes with major Information Retrieval and Information Extraction tasks and promotes multi-disciplinary research. In fact, it aims to provide support to three different usage roles: biologists, text miners and application developers.

::DEVELOPER

@Note team

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
MySQL

:: DOWNLOAD

@Note

:: MORE INFORMATION

Citation

Anália Lourenço , Rafael Carreira, Sónia Carneiro, Paulo Maia, Daniel Glez-Peña , Florentino Fdez-Riverola , Eugénio C Ferreira , Isabel Rocha and Miguel Rocha.
@Note: A workbench for Biomedical Text Mining.
Journal of Biomedical Informatics 2009, 42 710-720

BioLemmatizer 1.2 – Lemmatization tool for Morphological Processing of Biomedical Text

BioLemmatizer 1.2

:: DESCRIPTION

The BioLemmatizer is a domain-specific lemmatization tool for the morphological analysis of biomedical literature.

::DEVELOPER

BioLemmatizer team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Mac OsX / Linux
Java

:: DOWNLOAD

BioLemmatizer

:: MORE INFORMATION

Citation:

J Biomed Semantics. 2012 Apr 1;3:3. doi: 10.1186/2041-1480-3-3.
BioLemmatizer: a lemmatization tool for morphological processing of biomedical text.
Liu H1, Christiansen T, Baumgartner WA Jr, Verspoor K.

BioC 1.1 – A Minimalist Approach to Interoperability for Biomedical Text Processing

BioC 1.1

:: DESCRIPTION

BioC is a simple XML format to share text documents and annotations. It allows a large number of different annotations to be represented. We provide simple code to hold this data, read it and write it back to XML files, and perform some sample processing.

::DEVELOPER

BioC Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows/ MacOsX
Java / C++

:: DOWNLOAD

BioC

:: MORE INFORMATION

Citation

Database (Oxford). 2013 Sep 18;2013:bat064. doi: 10.1093/database/bat064. Print 2013.
BioC: a minimalist approach to interoperability for biomedical text processing.
Comeau DC, Islamaj Doğan R, Ciccarese P, Cohen KB, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M, Valencia A, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.

MetaMap 2020 – Mapping of Biomedical Text to the UMLS Metathesaurusext

MetaMap 2020

:: DESCRIPTION

MetaMap is a highly configurable program to map biomedical text to the UMLS Metathesaurus or, equivalently, to discover Metathesaurus concepts referred to in text. MetaMap uses a knowledge-intensive approach based on symbolic, natural-language processing (NLP) and computational-linguistic techniques. Besides being applied for both IR and data-mining applications, MetaMap is one of the foundations of NLM’s Medical Text Indexer (MTI) which is being used for both semiautomatic and fully automatic indexing of biomedical literature at NLM.

::DEVELOPER

Dr. Alan (Lan) Aronson at the National Library of Medicine (NLM)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Mac OsX / Linux /Windows

:: DOWNLOAD

MetaMap

:: MORE INFORMATION

Citation:

An overview of MetaMap: historical perspective and recent advances.
Aronson AR, Lang FM.
J Am Med Inform Assoc. 2010 May-Jun;17(3):229-36. doi: 10.1136/jamia.2009.002733.

SimConcept – Hybrid approach for simplifying Composite Named Entities in Biomedical Text

SimConcept

:: DESCRIPTION

SimConcept is a hybrid approach by integrating a machine learning model with a pattern identification strategy to identify individual mentions from a composite named entity.

::DEVELOPER

SimConcept team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows
Perl

:: DOWNLOAD

SimConcept

:: MORE INFORMATION

Citation

IEEE J Biomed Health Inform. 2015 Jul;19(4):1385-91. doi: 10.1109/JBHI.2015.2422651. Epub 2015 Apr 13.
SimConcept: a hybrid approach for simplifying composite named entities in biomedical text.
Wei CH, Leaman R, Lu Z.

text2genome 0.4 – Extract DNA Sequences from Biomedical Text

text2genome 0.4

:: DESCRIPTION

text2genome is using a unique way to map scientific articles to genomic locations: From a full-text scientific article and it’s supplementary data files, all words that resemble DNA sequences are extracted and then mapped to public genome sequences. They can then be displayed on genome browser websites and used in data-mining applications.

::DEVELOPER

the Bergman lab. Haussler lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

text2genome

:: MORE INFORMATION

Citation

Hauessler et al. (2011)
Annotating genes and genomes with DNA sequences extracted from biomedical articles
Bioinformatics (2011) 27 (7): 980-986.