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Genome wide in silico SNP-tumor association analysis
Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) record...
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Published in: | BMC cancer 2004-01, Vol.4 (1), p.4-4, Article 4 |
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container_title | BMC cancer |
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creator | Qiu, Ping Wang, Luquan Kostich, Mitch Ding, Wei Simon, Jason S Greene, Jonathan R |
description | Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue.
An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).
A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation
This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer. |
doi_str_mv | 10.1186/1471-2407-4-4 |
format | article |
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An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).
A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation
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An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).
A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation
This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.</description><subject>Databases, Genetic</subject><subject>Expressed Sequence Tags</subject><subject>Gene Frequency</subject><subject>National Library of Medicine (U.S.)</subject><subject>Neoplasms - genetics</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>United States</subject><issn>1471-2407</issn><issn>1471-2407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp1kctLJDEQxoO4-D56lT55azfpVDrJQVDEF8jugnoOlcdopLujSY_if78zzuA6LJ4qlfq-XyV8hOwzesSYan8ykKxugMoaalgjW5_9-pfzJtku5YlSJhVVG2STCUqFonKLwGUYUh-qt-hDFYeqxC66VN3--lOP0z7lCktJLuIY01DhgN17iWWX_JhgV8Lesu6Q-4vzu7Or-ub35fXZ6U1tBW_H2qvABNMOJ7ylTnLXMkQ6EeCd8LZxoD141WrqhWg0qsZrTq3nUkHLuPZ8h1wvuD7hk3nOscf8bhJG83GR8oPBPEbXBdMib7j3wC0NAOCt1NYJrawWDZOoZ6zjBet5avvgXRjGjN0KdHUyxEfzkF4NB96oZuY_WfhtTN_4Vycu9WYegJkHYMDADHG4fEJOL9NQRtPH4kLX4RDStBgmBecMxExYL4Qup1JymHyuYdTMU_8PfPD1b__Uy5j5X-Yop7U</recordid><startdate>20040129</startdate><enddate>20040129</enddate><creator>Qiu, Ping</creator><creator>Wang, Luquan</creator><creator>Kostich, Mitch</creator><creator>Ding, Wei</creator><creator>Simon, Jason S</creator><creator>Greene, Jonathan R</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TO</scope><scope>H94</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20040129</creationdate><title>Genome wide in silico SNP-tumor association analysis</title><author>Qiu, Ping ; Wang, Luquan ; Kostich, Mitch ; Ding, Wei ; Simon, Jason S ; Greene, Jonathan R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b536t-d8e1519caf360c73c61aa0f54dc5db2c49d4d8690d5529a82d930bd37846139d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Databases, Genetic</topic><topic>Expressed Sequence Tags</topic><topic>Gene Frequency</topic><topic>National Library of Medicine (U.S.)</topic><topic>Neoplasms - genetics</topic><topic>Polymorphism, Single Nucleotide - genetics</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qiu, Ping</creatorcontrib><creatorcontrib>Wang, Luquan</creatorcontrib><creatorcontrib>Kostich, Mitch</creatorcontrib><creatorcontrib>Ding, Wei</creatorcontrib><creatorcontrib>Simon, Jason S</creatorcontrib><creatorcontrib>Greene, Jonathan R</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>BMC cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Qiu, Ping</au><au>Wang, Luquan</au><au>Kostich, Mitch</au><au>Ding, Wei</au><au>Simon, Jason S</au><au>Greene, Jonathan R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genome wide in silico SNP-tumor association analysis</atitle><jtitle>BMC cancer</jtitle><addtitle>BMC Cancer</addtitle><date>2004-01-29</date><risdate>2004</risdate><volume>4</volume><issue>1</issue><spage>4</spage><epage>4</epage><pages>4-4</pages><artnum>4</artnum><issn>1471-2407</issn><eissn>1471-2407</eissn><abstract>Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue.
An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).
A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation
This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>15005807</pmid><doi>10.1186/1471-2407-4-4</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Databases, Genetic Expressed Sequence Tags Gene Frequency National Library of Medicine (U.S.) Neoplasms - genetics Polymorphism, Single Nucleotide - genetics United States |
title | Genome wide in silico SNP-tumor association analysis |
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