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Personal genomics, bioinformatics, and variomics

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</span><strong><span style="FONT-SIZE: 9pt">Jong Bhak, Ho Ghang, Rohit Reja,&nbsp;and Sangsoo Kim</span></strong><span style="FONT-SIZE: 9pt"><br />
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KOBIC (Korean Bioinformation Center), KRIBB, Daejeon, Korea. Dept. of Bioinformatics, Soongsil Univ., Seoul, Korea.<br /span><br /div>Correspondence: <div align="left"/span><span style="FONT-SIZE: 9pt"><a href="mailto:jongbhak@yahoo.com"><font color="#0000ff">jongbhak@yahoo.com</font></a>, sskimb@ssu.ac.kr</span></div>
<div align="left"><span style="FONT-SIZE: 9pt"><br />
</span><strong><span style="FONT-SIZE: 9pt">Abstract</span></strong><span style="FONT-SIZE: 9pt"><br />
</span></div>
<div align="left"><strong><span style="FONT-SIZE: 9pt">Human Variome Project (HVP)</span></strong></div>
<div p align="left"><span style="FONT-SIZE: 9pt">As an international collaboration, headed by Richard Cotton, HVP was launched in 2006 (<a href="http://humanvariomeproject.org/"><font color="#0000ff">http://humanvariomeproject.org</font></a>) </span><span style="FONT-SIZE: 9pt">(Ring, Kwok et al. 2006)</span><span style="FONT-SIZE: 9pt">. HVP aims to&nbsp;make clinicians who have been working on rare diseases, to work together with molecular biologists and bioinformaticians. Their goal is to link medical information with genotype information. Succinctly this process is called genotype to phenotype mapping. As several full human genome sequences are already available, mapping phenotypes to the full genomes will be the major challenge of biology in the next 20 years.&nbsp;<br />
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</span><strong><span style="FONT-SIZE: 9pt">Asian Variome Project (AVP)</span></strong><span style="FONT-SIZE: 9pt"><br />
Alongside and with the associations of eIMBL, A-IMBN, and HVP, a variome project that tries to map Asian population variome was launched in 2008. This was a group effort of Korean researchers who have been interested in genome sequences,&nbsp;SNPs, and CNVs. They have formed a Korean Variome Consortium (KOVAC: <a href="http://variome.kr/"><font color="#0000ff">http://variome.kr</font></a>) and supported AVP as one of the first projects. eIMBL that is the virtual lab laboratory network of Asia linking key biologists biology groups modeled after EMBL has acquired $80,000 USD in 2008 to support AVP. eIMBL aims to establish a virtual bioinformatics center in Asia pacific Pacific region that links many bioinformation processing scientists in Asia.<br />
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</span><strong><span style="FONT-SIZE: 9pt">Bioinformatics for personal genomes and variomes</span></strong><span style="FONT-SIZE: 9pt"><br />
Bioinformatics is the key in personal genome projects and variome projects. Bioinformatics is not a set of tools but it is a proper scientific discipline. It regards life as a gigantic information processing phenomenon and tries to map its components and to model the emerging networks of the components. Bioinformatics in 2008 is driving biology into an information science. Most biology researches are now with massive amount of data that can not cannot be processed by hand. Nearly all the biological research outcomes in the next&nbsp;five years will have some form of high throughput data such as genome sequences, microarray data, proteome analyses, SNPs, epigenome chips, and large scale phenotype mapping. Bioinformatics tools in genomics and variomics can be found from various internet resources. There are various bioinformatics hubs such as NCBI (National Center for Biotechnology Information), EBI (European Bioinformatics Institute), DDBJ (Databank of Japan), and KOBIC.&nbsp;Some&nbsp;others are: Bioinformatics Organization (<a href="http://bioinformatics.org/"><font color="#0000ff">http://Bioinformatics.Org</font></a>), EMBnet (<a href="http://www.embnet.org/"><font color="#0000ff">http://www.embnet.org/</font></a>), and&nbsp;The International Society for Computational Biology (<a href="http://iscb.org/"><font color="#0000ff">http://iscb.org</font></a>). The following are major bioinformatics journals:<br />
<br />
Algorithms in Molecular Biology (http://www.almob.org/)<br />
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</span><strong><span style="FONT-SIZE: 9pt">Mapping expression using DNA sequencing</span></strong><span style="FONT-SIZE: 9pt"><br />
DNA sequencing technology&nbsp;used to be&nbsp;for mapping genotypes. However, they are now used to map expression levels in cells. Cells produce various RNAs. mRNA is the most abundant and important. In the past, microarray and DNA chips were used for measuring expression levels. They are not accurate and it takes many bioinformatic adjustments before it becomes reliable expression data. New sequencing technologies can measure expression levels much more accurately. By sequencing the RNAs, we can now quantify the mRNA levels by precisely knowing the RNA sequences. Sequencing technologies will restructure the expression analyses in the future.</span></divp>
<div><strong><font size="2">Conclusion</font></strong><br />
<font size="2">In 2009 and onwards, personal genome projects will produce unprecedented amount of biological data. New bioinformatics technologies will be required to handle them. New sequencing technologies will drive the next decades of biology and transform the medical practices in hospitals within the next decades. Fast sequencing unexpectedly brought us interesting applications such as metagenomics and ecogenomics. </font><font size="2">We have examined the current trends in genomics and variomics.</font><br />
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</div>
<div><font size="2"><strong>References</strong></font></div>
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<div style="MARGIN: 0cm 0cm 0pt 36pt; TEXT-INDENT: -36pt">&nbsp;</div>
<div><font color="#ff6600">Park, H. et al. (2008). &quot;Genome-wide Linkage Study for Plasma HDL Cholesterol Level in an Isolated Population of Mongolia.&quot; Genomics &amp; Informatics 6(1): 8-13.<br />
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