recent advances in high - throughput sequencing technologies have enabled us to determine many genomic sequences quickly and cheaply .
the use of biological sequence information has greatly facilitated the r&d process in the pharmaceutical , agricultural , medical and chemical industries ( 1 ) .
sequences patent owners can gain tremendous value and control over the exploitation of the sequences ( 2 ) . over the past several decades , the number of patent applications containing nucleic acid or amino acid sequences has been increasing rapidly . for patent - related biological sequences , there are both public and commercial databases that provide patent information ( 3 ) .
public efforts are represented by genbank ( 4 ) , the european molecular biology laboratory ( embl ) ( 5 ) and the dna database of japan ( ddbj ) ( 6 ) .
genbank obtains patent sequences from the patents issued by the us patent and trademark office ( uspto ) .
the websites of these three public databases offer patent sequence data downloading , simple keyword searching and alignment searching .
in addition , patgen ( 7 ) , an integrated database containing sequence data from public resources , provides access to non - redundant sequence information , as well as an abstract service .
the commercial sector is led by chemical abstract service ( ) and derwent ( ) with their corresponding databases : cas registry and derwent geneseq .
although these patent databases provide good information on patent - related sequences , they have little biological information on the sequences , except for their organism information .
the mapping of the sequences and biological resources , such as gene and disease , will provide an opportunity for understanding of bio - resources ' patentable targets ( 8) . especially , patent - related gene information can be used to identify whether a particular gene has been patented or published and to reveal if a patent has been infringed upon ( 9 ) .
recently , jensen and murray ( 10 ) reported that 20% of human genes have been claimed as us intellectual property from the analysis of the sequences in us patents with bioinformatical methods .
however , they used only the sequences at genbank , and their analysis was focused on human genes . according to their knowledge ,
no attempt has been made to annotate the biological sequences in patents or applications thoroughly and to analyze them from a biological perspective . in this report , we describe patome , a database server containing the patent - related biological sequences and their analysis data .
to build patome , we downloaded sequence data from publicly available databases and created a non - redundant sequence set .
the non - redundant sequences were annotated with refseq ( 11 ) and associated with entrez gene ( 12 ) , the online mendelian inheritance in man ( omim ) ( 13 ) and gene ontology ( go ) ( 14 ) .
the annotation results and the analysis data were integrated into a relational database and served via web - based user interfaces .
we downloaded the sequences from the patent divisions of genbank ( ) , embl ( ) , and ddbj ( ) .
sequence data were also obtained from the world intellectual property organization ( wipo ) ( ) and the publication site for issued and published sequences ( psips ) database ( ) maintained by uspto . as psips does not provide a conventional ftp service , we downloaded sequence listings one - by - one from the psips search interface .
all the sequences obtained were derived from the sequence listings disclosed in the issued patents or published patent applications mainly in usa , japan , europe and by wipo .
we created a non - redundant sequence set by removing the redundancy in the five databases . if the sequences had the same publication number and the same seqid , they were considered duplicates . as on june 1 ,  2006 ,
the number of non - redundant sequences were 38  151  115 , including 34  762  740 nucleic acid sequences and 3  388  375 amino acid sequences . in the non - redundant sequences , there is a large number of short fragments , which are mostly primers or synthetic constructs .
therefore , we excluded the nucleic acids ( < 100 bases ) and the amino acids ( < 10 residues ) in a similarity - based annotation .
the sequence data also had many spelling errors and informal names in their organism fields .
they were corrected either by using ncbi taxonomy database or manually for use in the next process .
we developed an automated pipeline to identify the genes from which the disclosed sequences were derived ( figure 1 ) .
first , the nucleic acid sequences were compared with both the refseq mrna database and complete sequenced microbial mrna by using balstn ( 15 ) .
the amino acid sequences were compared with refseq proteins by using balstp . in the patent field ,
blast search is a general method that is used to identify functions of unknown sequences and to determine whether sequences are novel ( 16 ) .
the blast results were filtered by 98% identity and an e - value of 1  10 .
the blast results are filtered with three filtering methods : e - value & percent identity , organism comparison and coverage . from the mapping between the annotated data and biological database information ( gene ,
the patome database is constructed to store annotation and analysis data and to make this information available to users via web interfaces . in general , the blast program was widely used to identify cdnas or proteins similar to a query sequence by retrieving putative homologs with performing local alignments ( 17 ) .
thus , their results could have orthologous sequences of query sequences ( e.g. human query sequence matches with mouse sequences of refseq ) . in the study ,
the main purpose of blast searching is to find gene sequences of the query sequences .
therefore , we applied two additional filtering methods to the blast results , in order to remove orthologs and find the exact gene in the same organism as that of a query sequence .
first , we utilized the organism name of a query sequence , called an organism comparison method , in which an organism of the best hit refseq should be the same as that of the query sequence . by applying this method , spurious matches to orthologous genes
could be filtered out . however , this method could not be applied if a query 's organism was unknown .
if a sequence was derived from a gene sequence , it should either contain most of the gene sequence or be a part of it .
hence , we divided the blast results into two types according to the alignment coverage against refseq sequences .
the full - length type is defined if an alignment length is > 80% of that of the matched refseq sequence .
the partial - length type is defined if an alignment length is > 95% of that of the query sequence , except full - length types .
blast alignments should be either full - length or partial - length type to go through the filtering . from the filtered blast results ,
the sequence function was assigned with the best refseq hit . of the 8  471  504 nucleic acid sequences ,
1  075  764 ( 13% ) were annotated with refseq mrnas or microbial mrnas .
of the 2  470  671 amino acid sequences , 1  486  625 ( 50% ) were annotated with refseq proteins .
the filtered blast results were saved as an annotation table that consists of the patent information ( publication and seqid ) and the annotation information ( refseq number , alignment length , alignment coverage and type , and e - value ) .
refseq numbers of the annotation table served as a bridge to link the disclosed sequences and gene information , whose association can be represented as a gene 
patent table that contains genes and their related patent sequence information . to build the gene 
patent table , we extracted linking information between the sequences and the corresponding refseq number from the annotation table , and their relationship was translated to a gene 
entrez gene also has cross - link information to other biological databases represented by gene2go and mim2gene files .
for example , if two sequences from a  seqid 39020 of wo0171042 and a  seqid 20352 of us6703491 are assigned a refseq number , 
nm_143536 , in the annotation table , it means that the refseq number ,  nm_143536 , was linked to the two sequences . as the refseq number , 
nm_143536 was cross - linked with a geneid  43614 in the gene2refseq , we can conclude that the geneid , 
43614 was disclosed twice in issued patents or patent applications . from the analysis of the sequences
, we found that 55% of the human genes were associated with patents or patent applications , the highest percentage among organisms .
oryza sativa ( rice ) ranked second with 25% ( 12  045 genes ) .
the summary of patent - related genes in the major organisms is shown in table 1 .
for the gene  patent analysis , it is necessary to distinguish sequences of granted patents from those of patent applications ( 18 ) .
in this study , the sequences were derived from either issued patents or published patent applications .
accordingly , it can not be guaranteed that the genes appearing in the gene  patent table are patented .
summary of patent - related genes in the major organisms the number of genes is from ncbi entrez gene .
we downloaded the sequences from the patent divisions of genbank ( ) , embl ( ) , and ddbj ( ) .
sequence data were also obtained from the world intellectual property organization ( wipo ) ( ) and the publication site for issued and published sequences ( psips ) database ( ) maintained by uspto . as psips does not provide a conventional ftp service , we downloaded sequence listings one - by - one from the psips search interface .
all the sequences obtained were derived from the sequence listings disclosed in the issued patents or published patent applications mainly in usa , japan , europe and by wipo .
we created a non - redundant sequence set by removing the redundancy in the five databases . if the sequences had the same publication number and the same seqid , they were considered duplicates . as on june 1 ,  2006 ,
the number of non - redundant sequences were 38  151  115 , including 34  762  740 nucleic acid sequences and 3  388  375 amino acid sequences . in the non - redundant sequences , there is a large number of short fragments , which are mostly primers or synthetic constructs .
therefore , we excluded the nucleic acids ( < 100 bases ) and the amino acids ( < 10 residues ) in a similarity - based annotation .
the sequence data also had many spelling errors and informal names in their organism fields .
they were corrected either by using ncbi taxonomy database or manually for use in the next process .
we developed an automated pipeline to identify the genes from which the disclosed sequences were derived ( figure 1 ) .
first , the nucleic acid sequences were compared with both the refseq mrna database and complete sequenced microbial mrna by using balstn ( 15 ) .
the amino acid sequences were compared with refseq proteins by using balstp . in the patent field ,
blast search is a general method that is used to identify functions of unknown sequences and to determine whether sequences are novel ( 16 ) .
the blast results were filtered by 98% identity and an e - value of 1  10 .
the blast results are filtered with three filtering methods : e - value & percent identity , organism comparison and coverage . from the mapping between the annotated data and biological database information ( gene ,
the patome database is constructed to store annotation and analysis data and to make this information available to users via web interfaces . in general , the blast program was widely used to identify cdnas or proteins similar to a query sequence by retrieving putative homologs with performing local alignments ( 17 ) .
thus , their results could have orthologous sequences of query sequences ( e.g. human query sequence matches with mouse sequences of refseq ) . in the study ,
the main purpose of blast searching is to find gene sequences of the query sequences .
therefore , we applied two additional filtering methods to the blast results , in order to remove orthologs and find the exact gene in the same organism as that of a query sequence .
first , we utilized the organism name of a query sequence , called an organism comparison method , in which an organism of the best hit refseq should be the same as that of the query sequence . by applying this method , spurious matches to orthologous genes
could be filtered out . however , this method could not be applied if a query 's organism was unknown .
if a sequence was derived from a gene sequence , it should either contain most of the gene sequence or be a part of it .
hence , we divided the blast results into two types according to the alignment coverage against refseq sequences .
the full - length type is defined if an alignment length is > 80% of that of the matched refseq sequence .
the partial - length type is defined if an alignment length is > 95% of that of the query sequence , except full - length types .
blast alignments should be either full - length or partial - length type to go through the filtering . from the filtered blast results ,
the sequence function was assigned with the best refseq hit . of the 8  471  504 nucleic acid sequences ,
1  075  764 ( 13% ) were annotated with refseq mrnas or microbial mrnas .
of the 2  470  671 amino acid sequences , 1  486  625 ( 50% ) were annotated with refseq proteins .
the filtered blast results were saved as an annotation table that consists of the patent information ( publication and seqid ) and the annotation information ( refseq number , alignment length , alignment coverage and type , and e - value ) .
refseq numbers of the annotation table served as a bridge to link the disclosed sequences and gene information , whose association can be represented as a gene 
patent table that contains genes and their related patent sequence information . to build the gene 
patent table , we extracted linking information between the sequences and the corresponding refseq number from the annotation table , and their relationship was translated to a gene  patent table by using a gene2refseq file from the entrez gene database .
entrez gene also has cross - link information to other biological databases represented by gene2go and mim2gene files .
for example , if two sequences from a  seqid 39020 of wo0171042 and a  seqid 20352 of us6703491 are assigned a refseq number , 
nm_143536 , in the annotation table , it means that the refseq number ,  nm_143536 , was linked to the two sequences . as the refseq number , 
nm_143536 was cross - linked with a geneid  43614 in the gene2refseq , we can conclude that the geneid , 
43614 was disclosed twice in issued patents or patent applications . from the analysis of the sequences
, we found that 55% of the human genes were associated with patents or patent applications , the highest percentage among organisms .
oryza sativa ( rice ) ranked second with 25% ( 12  045 genes ) .
the summary of patent - related genes in the major organisms is shown in table 1 .
for the gene  patent analysis , it is necessary to distinguish sequences of granted patents from those of patent applications ( 18 ) .
in this study , the sequences were derived from either issued patents or published patent applications .
accordingly , it can not be guaranteed that the genes appearing in the gene  patent table are patented .
summary of patent - related genes in the major organisms the number of genes is from ncbi entrez gene .
patome database server is composed of a web interface and an mysql database management system .
the web interface is implemented in static html pages , java server pages ( jsp ) ( ) and servlet ( ) programs for database searching .
mysql is used to store the disclosed sequence information and their annotation and analysis data .
the querying interface allows the user to search against the patent sequence data and their analysis data .
the patent sequence data can be searched by patent ( or application ) number , genbank accession number and title .
the search results consist of sequence information ( length , type , organism , sequence ) , annotation information ( refseq , gene , go , omim , coverage ) if it exists and the same sequences information as a query .
the analysis data search interface allows the user to search for the gene name ( or symbol ) , entrez gene i d and refseq number . in addition , the logical operators , or (  ) and and ( & ) , can be used to combine search words in the title and gene searches .
( b ) output of both patent ( or application ) number and seqid search .
the display of search results also contains outgoing links to external databases for sequences and patents .
for example , patent ( or application ) numbers are linked to the uspto database ( ) for us patents or applications , and the esp@cenet patent database server ( ) at the european patent office for the others .
gene names in the search output are linked to entrez gene and reactome ( 19 ) .
the data are presented in simple tab - delimited text file ( for easy parsing of the data ) .
this includes the national ( including wipo ) , length and organism distributions of the sequences .
we also present statistics on gene - associated patents of major organisms in the homepage .
 with the advent of automated and high - throughput techniques , the number of patent applications containing biological sequences has been increasing rapidly . 
 however , they have attracted relatively little attention compared to other sequence resources . 
 we have built a database server called patome , which contains biological sequence data disclosed in patents and published applications , as well as their analysis information . 
 the analysis is divided into two steps . 
 the first is an annotation step in which the disclosed sequences were annotated with refseq database . 
 the second is an association step where the sequences were linked to entrez gene , omim and go databases , and their results were saved as a gene  patent table . from the analysis 
 , we found that 55% of human genes were associated with patenting . the gene  
 patent table can be used to identify whether a particular gene or disease is related to patenting 
 . patome is available at ; the information is updated bimonthly . 
INTRODUCTION
DATABASE CONTENTS AND ANALYSIS PIPELINE
Dataset
Annotating the disclosed sequences
Building a genepatent association table
SEARCHING AND DOWNLOADING THE PATOME DATABASE