Skip to content

Advertisement

You're viewing the new version of our site. Please leave us feedback.

Learn more

BMC Bioinformatics

Volume 6 Supplement 1

A critical assessment of text mining methods in molecular biology

Reports

Edited by Christian Blaschke, Lynette Hirschman, Alfonso Valencia, Alexander Yeh

A critical assessment of text mining methods in molecular biology. Go to conference site.

Granada, SpainMarch 28-31, 2004

Previous Page Page 1 of 2 Next Page
  1. Content type: Introduction

    The goal of the first BioCreAtIvE challenge (Critical Assessment of Information Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of the art for text mining applied to ...

    Authors: Lynette Hirschman, Alexander Yeh, Christian Blaschke and Alfonso Valencia

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S1

    Published on:

  2. Content type: Report

    The biological research literature is a major repository of knowledge. As the amount of literature increases, it will get harder to find the information of interest on a particular topic. There has been an inc...

    Authors: Alexander Yeh, Alexander Morgan, Marc Colosimo and Lynette Hirschman

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S2

    Published on:

  3. Content type: Report

    Named entity recognition (NER) is an important first step for text mining the biomedical literature. Evaluating the performance of biomedical NER systems is impossible without a standardized test corpus. The a...

    Authors: Lorraine Tanabe, Natalie Xie, Lynne H Thom, Wayne Matten and W John Wilbur

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S3

    Published on:

  4. Content type: Report

    Our approach to Task 1A was inspired by Tanabe and Wilbur's ABGene system [1, 2]. Like Tanabe and Wilbur, we approached the problem as one of part-of-speech tagging, adding a GENE tag to the standard tag set. Whe...

    Authors: Shuhei Kinoshita, K Bretonnel Cohen, Philip V Ogren and Lawrence Hunter

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S4

    Published on:

  5. Content type: Report

    Good automatic information extraction tools offer hope for automatic processing of the exploding biomedical literature, and successful named entity recognition is a key component for such tools.

    Authors: Jenny Finkel, Shipra Dingare, Christopher D Manning, Malvina Nissim, Beatrice Alex and Claire Grover

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S5

    Published on:

  6. Content type: Report

    Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedical named entities is the first step in inf...

    Authors: Tomohiro Mitsumori, Sevrani Fation, Masaki Murata, Kouichi Doi and Hirohumi Doi

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S8

    Published on:

  7. Content type: Report

    In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural language sentences. We approach this problem by building a word cla...

    Authors: Jörg Hakenberg, Steffen Bickel, Conrad Plake, Ulf Brefeld, Hagen Zahn, Lukas Faulstich, Ulf Leser and Tobias Scheffer

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S9

    Published on:

  8. Content type: Report

    Our goal in BioCreAtIve has been to assess the state of the art in text mining, with emphasis on applications that reflect real biological applications, e.g., the curation process for model organism databases....

    Authors: Lynette Hirschman, Marc Colosimo, Alexander Morgan and Alexander Yeh

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S11

    Published on:

  9. Content type: Report

    We prepared and evaluated training and test materials for an assessment of text mining methods in molecular biology. The goal of the assessment was to evaluate the ability of automated systems to generate a li...

    Authors: Marc E Colosimo, Alexander A Morgan, Alexander S Yeh, Jeffrey B Colombe and Lynette Hirschman

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S12

    Published on:

  10. Content type: Report

    Document gene normalization is the problem of creating a list of unique identifiers for genes that are mentioned within a document. Automating this process has many potential applications in both information e...

    Authors: Jeremiah Crim, Ryan McDonald and Fernando Pereira

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S13

    Published on:

  11. Content type: Report

    Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple synonyms for individual genes and proteins, a...

    Authors: Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevissen, Ralf Zimmer and Juliane Fluck

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S14

    Published on:

  12. Content type: Report

    Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and store...

    Authors: Christian Blaschke, Eduardo Andres Leon, Martin Krallinger and Alfonso Valencia

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S16

    Published on:

  13. Content type: Report

    We participated in the BioCreAtIvE Task 2, which addressed the annotation of proteins into the Gene Ontology (GO) based on the text of a given document and the selection of evidence text from the document just...

    Authors: Karin Verspoor, Judith Cohn, Cliff Joslyn, Sue Mniszewski, Andreas Rechtsteiner, Luis M Rocha and Tiago Simas

    Citation: BMC Bioinformatics 2005 6(Suppl 1):S20

    Published on:

Previous Page Page 1 of 2 Next Page