Advancing Science through Mining Libraries, Ontologies, and Communities*

@article{Evans2011AdvancingST,
  title={Advancing Science through Mining Libraries, Ontologies, and Communities*},
  author={James A. Evans and A. Rzhetsky},
  journal={The Journal of Biological Chemistry},
  year={2011},
  volume={286},
  pages={23659 - 23666}
}
Life scientists today cannot hope to read everything relevant to their research. Emerging text-mining tools can help by identifying topics and distilling statements from books and articles with increased accuracy. Researchers often organize these statements into ontologies, consistent systems of reality claims. Like scientific thinking and interchange, however, text-mined information (even when accurately captured) is complex, redundant, sometimes incoherent, and often contradictory: it is… 
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14 Citations
Background Citations
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Methods Citations
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14 Citations

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References

SHOWING 1-10 OF 38 REFERENCES
Strategic Reading, Ontologies, and the Future of Scientific Publishing
TLDR
How scientists use new forms of the “literature” and how the ascendance of novel computing technologies will combine to revolutionize the way scientific data is accessed, synthesized, and turned to practical use are reviewed.
Rutabaga by any other name: extracting biological names
Using statistical and knowledge-based approaches for literature-based discovery
Infotopia: How Many Minds Produce Knowledge
This book explores the human potential to pool widely dispersed information, and to use that knowledge to improve both our institutions and our lives. Various methods for aggregating information are…
A translation approach to portable ontology specifications
TLDR
This paper describes a mechanism for defining ontologies that are portable over representation systems, basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Microparadigms: chains of collective reasoning in publications about molecular interactions.
TLDR
It is found that published statements, regardless of their verity, tend to interfere with interpretation of the subsequent experiments and, therefore, can act as scientific "microparadigms," similar to dominant scientific theories.
How citation distortions create unfounded authority: analysis of a citation network
TLDR
Citation is both an impartial scholarly method and a powerful form of social communication that can be used to generate information cascades resulting in unfounded authority of claims.
GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles
TLDR
A system is presented that extracts and structures information about cellular pathways from the biological literature in accordance with a knowledge model that was developed earlier and implemented by modifying an existing medical natural language processing system.
Biomedical Discovery Acceleration, with Applications to Craniofacial Development
TLDR
A novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data, is described and demonstrated on a large-scale gene expression array dataset relevant to craniofacial development.
The outcomes of pathway database computations depend on pathway ontology
TLDR
Compared KEGG and BioCyc pathways are compared using genome context methods, which determine the functional relatedness of pairs of genes, supporting the conclusion that theBioCyc pathway conceptualization is closer to a single conserved biological process than is that of K EGG.
...
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