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PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins
BACKGROUND: The number of patents associated with genes and proteins and the amount of information contained in each patent often present a real obstacle to the rapid evaluation of the novelty of findings associated to genes from an intellectual property (IP) perspective. This assessment, normally c...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2025596/ https://www.ncbi.nlm.nih.gov/pubmed/17822555 http://dx.doi.org/10.1186/1751-0473-2-4 |
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author | Lahm, Armin de Rinaldis, Emanuele |
author_facet | Lahm, Armin de Rinaldis, Emanuele |
author_sort | Lahm, Armin |
collection | PubMed |
description | BACKGROUND: The number of patents associated with genes and proteins and the amount of information contained in each patent often present a real obstacle to the rapid evaluation of the novelty of findings associated to genes from an intellectual property (IP) perspective. This assessment, normally carried out by expert patent professionals, can therefore become cumbersome and time consuming. Here we present PatentMatrix, a novel software tool for the automated analysis of patent sequence text entries. METHODS AND RESULTS: PatentMatrix is written in the Awk language and requires installation of the Derwent GENESEQ™ patent sequence database under the sequence retrieval system SRS. The software works by taking as input two files: i) a list of genes or proteins with the associated GENESEQ™ patent sequence accession numbers ii) a list of keywords describing the research context of interest (e.g. 'lung', 'cancer', 'therapeutics', 'diagnostics'). The GENESEQ™ database is interrogated through the SRS system and each patent entry of interest is screened for the occurrence of user-defined keywords. Moreover, the software extracts the basic information useful for a preliminary assessment of the IP coverage of each patent from the GENESEQ™ database. As output, two tab-delimited files are generated which provide the user with a detailed and an aggregated view of the results. An example is given where the IP position of five genes is evaluated in the context of 'development of antibodies for cancer treatment' CONCLUSION: PatentMatrix allows a rapid survey of patents associated with genes or proteins in a particular area of interest as defined by keywords. It can be efficiently used to evaluate the IP-related novelty of scientific findings and to rank genes or proteins according to their IP position. |
format | Text |
id | pubmed-2025596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-20255962007-10-16 PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins Lahm, Armin de Rinaldis, Emanuele Source Code Biol Med Methodology BACKGROUND: The number of patents associated with genes and proteins and the amount of information contained in each patent often present a real obstacle to the rapid evaluation of the novelty of findings associated to genes from an intellectual property (IP) perspective. This assessment, normally carried out by expert patent professionals, can therefore become cumbersome and time consuming. Here we present PatentMatrix, a novel software tool for the automated analysis of patent sequence text entries. METHODS AND RESULTS: PatentMatrix is written in the Awk language and requires installation of the Derwent GENESEQ™ patent sequence database under the sequence retrieval system SRS. The software works by taking as input two files: i) a list of genes or proteins with the associated GENESEQ™ patent sequence accession numbers ii) a list of keywords describing the research context of interest (e.g. 'lung', 'cancer', 'therapeutics', 'diagnostics'). The GENESEQ™ database is interrogated through the SRS system and each patent entry of interest is screened for the occurrence of user-defined keywords. Moreover, the software extracts the basic information useful for a preliminary assessment of the IP coverage of each patent from the GENESEQ™ database. As output, two tab-delimited files are generated which provide the user with a detailed and an aggregated view of the results. An example is given where the IP position of five genes is evaluated in the context of 'development of antibodies for cancer treatment' CONCLUSION: PatentMatrix allows a rapid survey of patents associated with genes or proteins in a particular area of interest as defined by keywords. It can be efficiently used to evaluate the IP-related novelty of scientific findings and to rank genes or proteins according to their IP position. BioMed Central 2007-09-06 /pmc/articles/PMC2025596/ /pubmed/17822555 http://dx.doi.org/10.1186/1751-0473-2-4 Text en Copyright © 2007 Lahm and de Rinaldis; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Lahm, Armin de Rinaldis, Emanuele PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title | PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title_full | PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title_fullStr | PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title_full_unstemmed | PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title_short | PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins |
title_sort | patentmatrix: an automated tool to survey patents related to large sets of genes or proteins |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2025596/ https://www.ncbi.nlm.nih.gov/pubmed/17822555 http://dx.doi.org/10.1186/1751-0473-2-4 |
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