Medical abstract text mining papers

  1. New
    1. Associating Genes with Gene Ontology Codes Using a Maximum Entropy Analysis of Biomedical Literature
    2. ARROGANT: An application to manipulate large gene collections
    3. A shallow parser based on closed-class words to capture relations in biomedical text
      • Gondy Leroy, Hsinchun Chen, and Jesse D. Martinez, Jan 2003
      • leroy.pdf
    4. A vocabulary development and visualization tool based on natural language processing and the mining of textual patient reports

  2. PubGene
    1. A literature network of human genes for high-throughput analysis of gene expression
    2. Associations betwee gene expressions in breast cancer and patient survival
    3. Gene Expression Levels in Different Stages of Progression in Oral Squamous Cell Carcinoma

  3. Gene-Disease Corellation
    1. Analysis of Genomic and Proteomic Data Using Advanced Literature Mining
    2. Association of genes to genetically inherited diseases using data mining

  4. Gene-Gene Relation
    1. A method for finding communities of related genes
    2. Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network
    3. Mining microarray expression data by literature profiling
    4. A literature network of human genes for high-throughput analysis of gene expression
    5. Use of keyword hierarchies to interpret gene expression patterns
    6. Using text analysis to Identify Functionally Coherent Gene Groups
    7. BioBibliometrics:Information retrieval and visualization from co-occurrences of gene names in medline abstracts
    8. Identifying the Interaction between Genes and Gene Products Based on Frequently Seen Verbs in Medline Abstracts
      • Takeshi Sekimizu, Hyun S. Park, Jun'ichi Tsujii, 1998
      • sekimizu.pdf
    9. Methods for Large-Scale Mining of Networks of Human Genes

  5. Protein Interactions
    1. Automated extraction of information on protein-protein interactions from the biological literature
    2. Mining literature for protein-protein interactions
    3. Automatic Extraction of Protein Interactions from Scientific Abstracts
    4. PreBIND and Textomy - mining the biomedical literature for protein-protein interactions using a support vector machine
    5. Computer-Assisted Generation of a Protein- Interaction Database for Nuclear Receptors
    6. Extraction of protein interaction information from unstructured text using a context-free grammar
      • Joshua M. Temkin and Mark R. Gilder, Apr 2003
      • temkin.pdf

    7. Applications:
      Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts PIES, a Protein Interaction Extraction System EDGAR: Extraction of Drugs, Genes and Relations from the Biomedical Literature
      • T.C. Rindflesch, Lorraine Tanabe, John N. Weinstein, and L. Hunter; Pacific Symposium on Biocomputing 5:514-525 (2000)
      • rindflesch.pdf

  6. Protein Function
    1. Protein Structures and Information Extraction from Biological Texts: The PASTA System

  7. Gene relation to biological function
    1. The computational analysis of scientific literature to define and recognize gene expression clusters
    2. Use of keword hierarchies to interpret gene expression patterns
    3. Detecting gene relations from medline abstracts

  8. Enzyme Binding
    1. Mining Molecular Binding Terminology from Biomedical Text

  9. Pathways (Full text search)
    1. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles

  10. General
    1. Mining the Biomedical Literature in the Genomic Era: An Overview
    2. Mining the bibliome: searching for a needle in a haystack? (report)
    3. Accomplishments and challenges in literature data mining for biology
    4. Genomics and Natural Language Processing
      • Mark D. Yandell and William H.Majoros, Aug 2002
      • yandell.pdf
    5. Getting to the (c)ore of knowledge: mining biomedical literature
    6. Toward Information Extraction: Identifying protein names from biological papers
      • K. Fukuda, T. Tsunoda, A. Tamura, T. Takagi, 1998
      • fukuda.pdf
    7. Finding relevant references to genes and proteins in Medline using a Bayesian approach
    8. Mining MEDLINE: Abstracts, Sentences, Or Phrases?
      • J. Ding, D. Berleant, D. Nettleton, E. Wurtele, 2002
      • ding.pdf
    9. Genes, Themes and Microarrays Using Information Retrieval for Large-Scale Gene Analysis