Medical abstract text mining papers
- New
- Associating Genes with Gene Ontology Codes Using a Maximum Entropy Analysis of Biomedical Literature
- ARROGANT: An application to manipulate large gene collections
- 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
- A vocabulary development and visualization tool based on natural language processing and the mining of textual patient reports
- PubGene
- A literature network of human genes for high-throughput analysis of gene expression
- Associations betwee gene expressions in breast cancer and patient survival
- Gene Expression Levels in Different Stages of Progression in Oral Squamous Cell Carcinoma
- Gene-Disease Corellation
- Analysis of Genomic and Proteomic Data Using Advanced Literature Mining
- Association of genes to genetically inherited diseases using data mining
- Gene-Gene Relation
- A method for finding communities of related genes
- Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network
- Mining microarray expression data by literature profiling
- A literature network of human genes for high-throughput analysis of gene expression
- Use of keyword hierarchies to interpret gene expression patterns
- Using text analysis to Identify Functionally Coherent Gene Groups
- BioBibliometrics:Information retrieval and visualization from co-occurrences of gene names in medline abstracts
- 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
- Methods for Large-Scale Mining of Networks of Human Genes
- Protein Interactions
- Automated extraction of information on protein-protein interactions from the biological literature
- Mining literature for protein-protein interactions
- Automatic Extraction of Protein Interactions from Scientific Abstracts
- PreBIND and Textomy - mining the biomedical literature for protein-protein interactions using a support vector machine
- Computer-Assisted Generation of a Protein- Interaction Database for Nuclear Receptors
- Extraction of protein interaction information from unstructured text using a context-free grammar
- Joshua M. Temkin and Mark R. Gilder, Apr 2003
- temkin.pdf
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
- Protein Function
- Protein Structures and Information Extraction from Biological Texts:
The PASTA System
- Gene relation to biological function
- The computational analysis of scientific literature to define and recognize gene expression clusters
- Use of keword hierarchies to interpret gene expression patterns
- Detecting gene relations from medline abstracts
- Enzyme Binding
- Mining Molecular Binding Terminology from Biomedical Text
- Pathways (Full text search)
- GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles
- General
- Mining the Biomedical Literature in the Genomic Era: An Overview
- Mining the bibliome: searching for a needle in a haystack? (report)
- Accomplishments and challenges in literature data mining for biology
- Genomics and Natural Language Processing
- Mark D. Yandell and William H.Majoros, Aug 2002
- yandell.pdf
- Getting to the (c)ore of knowledge: mining biomedical literature
- Toward Information Extraction: Identifying protein names from biological papers
- K. Fukuda, T. Tsunoda, A. Tamura, T. Takagi, 1998
- fukuda.pdf
- Finding relevant references to genes and proteins in Medline using a Bayesian approach
- Mining MEDLINE: Abstracts, Sentences, Or Phrases?
- J. Ding, D. Berleant, D. Nettleton, E. Wurtele, 2002
- ding.pdf
- Genes, Themes and Microarrays Using Information Retrieval for Large-Scale Gene Analysis