Nucleic Acids Research Advance Access originally published online on May 5, 2009
Nucleic Acids Research 2009 37(Web Server issue):W135-W140; doi:10.1093/nar/gkp303
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Nucleic Acids Research, 2009, Vol. 37, No. suppl_2 W135-W140
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Articles |
LitInspector: literature and signal transduction pathway mining in PubMed abstracts
Genomatix Software, 80335 Munich, Germany
*To whom correspondence should be addressed. Tel: +49 89 599 766 14; Fax: +49 89 599 766 55; Email: frisch{at}genomatix.de
Received January 30, 2009. Revised April 15, 2009. Accepted April 15, 2009.
LitInspector is a literature search tool providing gene and signal transduction pathway mining within NCBI's PubMed database. The automatic gene recognition and color coding increases the readability of abstracts and significantly speeds up literature research. A main challenge in gene recognition is the resolution of homonyms and rejection of identical abbreviations used in a ‘non-gene’ context. LitInspector uses automatically generated and manually refined filtering lists for this purpose. The quality of the LitInspector results was assessed with a published dataset of 181 PubMed sentences. LitInspector achieved a precision of 96.8%, a recall of 86.6% and an F-measure of 91.4%. To further demonstrate the homonym resolution qualities, LitInspector was compared to three other literature search tools using some challenging examples. The homonym MIZ-1 (gene IDs 7709 and 9063) was correctly resolved in 87% of the abstracts by LitInspector, whereas the other tools achieved recognition rates between 35% and 67%. The LitInspector signal transduction pathway mining is based on a manually curated database of pathway names (e.g. wingless type), pathway components (e.g. WNT1, FZD1), and general pathway keywords (e.g. signaling cascade). The performance was checked for 10 randomly selected genes. Eighty-two per cent of the 38 predicted pathway associations were correct. LitInspector is freely available at http://www.litinspector.org/.