Bio-Inspired Microsystem for Robust Genetic Assay Recognition
Identifieur interne : 000B20 ( Main/Exploration ); précédent : 000B19; suivant : 000B21Bio-Inspired Microsystem for Robust Genetic Assay Recognition
Auteurs : Jaw-Chyng Lue [États-Unis] ; Wai-Chi Fang [République populaire de Chine]Source :
- Journal of Biomedicine and Biotechnology [ 1110-7243 ] ; 2008.
Abstract
A compact integrated system-on-chip (SoC) architecture solution for robust, real-time, and on-site genetic analysis has been proposed. This microsystem solution is noise-tolerable and suitable for analyzing the weak fluorescence patterns from a PCR prepared dual-labeled DNA microchip assay. In the architecture, a preceding VLSI differential logarithm microchip is designed for effectively computing the logarithm of the normalized input fluorescence signals. A posterior VLSI artificial neural network (ANN) processor chip is used for analyzing the processed signals from the differential logarithm stage. A single-channel logarithmic circuit was fabricated and characterized. A prototype ANN chip with unsupervised winner-take-all (WTA) function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the supervised backpropagation (BP) algorithm is proposed for robustly recognizing low-intensity patterns. Our results show that the trained new ANN can recognize low-fluorescence patterns better than an ANN using the conventional sigmoid function.
Url:
DOI: 10.1155/2008/259174
PubMed: 18566679
PubMed Central: 2426746
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Pmc, to step Corpus: 000092
- to stream Pmc, to step Curation: 000092
- to stream Pmc, to step Checkpoint: 000174
- to stream Ncbi, to step Merge: 000053
- to stream Ncbi, to step Curation: 000053
- to stream Ncbi, to step Checkpoint: 000053
- to stream Main, to step Merge: 000B32
- to stream Main, to step Curation: 000B20
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Bio-Inspired Microsystem for Robust Genetic Assay Recognition</title>
<author><name sortKey="Lue, Jaw Chyng" sort="Lue, Jaw Chyng" uniqKey="Lue J" first="Jaw-Chyng" last="Lue">Jaw-Chyng Lue</name>
<affiliation wicri:level="4"><nlm:aff id="I1">Department of Electrical Engineering - Electrophysics, University of Southern California, Los Angeles, CA 90089, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Electrical Engineering - Electrophysics, University of Southern California, Los Angeles, CA 90089</wicri:regionArea>
<placeName><region type="state">Californie</region>
<settlement type="city">Los Angeles</settlement>
</placeName>
<orgName type="university">Université de Californie du Sud</orgName>
</affiliation>
</author>
<author><name sortKey="Fang, Wai Chi" sort="Fang, Wai Chi" uniqKey="Fang W" first="Wai-Chi" last="Fang">Wai-Chi Fang</name>
<affiliation wicri:level="1"><nlm:aff id="I2">Department of Electronics Egineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300, China</nlm:aff>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Department of Electronics Egineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300</wicri:regionArea>
<wicri:noRegion>Taiwan 300</wicri:noRegion>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">18566679</idno>
<idno type="pmc">2426746</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2426746</idno>
<idno type="RBID">PMC:2426746</idno>
<idno type="doi">10.1155/2008/259174</idno>
<date when="2008">2008</date>
<idno type="wicri:Area/Pmc/Corpus">000092</idno>
<idno type="wicri:Area/Pmc/Curation">000092</idno>
<idno type="wicri:Area/Pmc/Checkpoint">000174</idno>
<idno type="wicri:Area/Ncbi/Merge">000053</idno>
<idno type="wicri:Area/Ncbi/Curation">000053</idno>
<idno type="wicri:Area/Ncbi/Checkpoint">000053</idno>
<idno type="wicri:doubleKey">1110-7243:2008:Lue J:bio:inspired:microsystem</idno>
<idno type="wicri:Area/Main/Merge">000B32</idno>
<idno type="wicri:Area/Main/Curation">000B20</idno>
<idno type="wicri:Area/Main/Exploration">000B20</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Bio-Inspired Microsystem for Robust Genetic Assay Recognition</title>
<author><name sortKey="Lue, Jaw Chyng" sort="Lue, Jaw Chyng" uniqKey="Lue J" first="Jaw-Chyng" last="Lue">Jaw-Chyng Lue</name>
<affiliation wicri:level="4"><nlm:aff id="I1">Department of Electrical Engineering - Electrophysics, University of Southern California, Los Angeles, CA 90089, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Electrical Engineering - Electrophysics, University of Southern California, Los Angeles, CA 90089</wicri:regionArea>
<placeName><region type="state">Californie</region>
<settlement type="city">Los Angeles</settlement>
</placeName>
<orgName type="university">Université de Californie du Sud</orgName>
</affiliation>
</author>
<author><name sortKey="Fang, Wai Chi" sort="Fang, Wai Chi" uniqKey="Fang W" first="Wai-Chi" last="Fang">Wai-Chi Fang</name>
<affiliation wicri:level="1"><nlm:aff id="I2">Department of Electronics Egineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300, China</nlm:aff>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Department of Electronics Egineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300</wicri:regionArea>
<wicri:noRegion>Taiwan 300</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series><title level="j">Journal of Biomedicine and Biotechnology</title>
<idno type="ISSN">1110-7243</idno>
<idno type="eISSN">1110-7251</idno>
<imprint><date when="2008">2008</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p>A compact integrated system-on-chip (SoC) architecture solution for robust, real-time, and on-site genetic analysis has been proposed. This microsystem solution is noise-tolerable and suitable for analyzing the weak fluorescence patterns from a PCR prepared dual-labeled DNA microchip assay. In the architecture, a preceding VLSI differential logarithm microchip is designed for effectively computing the logarithm of the normalized input fluorescence signals. A posterior VLSI artificial neural network (ANN) processor chip is used for analyzing the processed signals from the differential logarithm stage. A single-channel logarithmic circuit was fabricated and characterized. A prototype ANN chip with unsupervised winner-take-all (WTA) function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the supervised backpropagation (BP) algorithm is proposed for robustly recognizing low-intensity patterns. Our results show that the trained new ANN can recognize low-fluorescence patterns better than an ANN using the conventional sigmoid function.</p>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<affiliations><list><country><li>République populaire de Chine</li>
<li>États-Unis</li>
</country>
<region><li>Californie</li>
</region>
<settlement><li>Los Angeles</li>
</settlement>
<orgName><li>Université de Californie du Sud</li>
</orgName>
</list>
<tree><country name="États-Unis"><region name="Californie"><name sortKey="Lue, Jaw Chyng" sort="Lue, Jaw Chyng" uniqKey="Lue J" first="Jaw-Chyng" last="Lue">Jaw-Chyng Lue</name>
</region>
</country>
<country name="République populaire de Chine"><noRegion><name sortKey="Fang, Wai Chi" sort="Fang, Wai Chi" uniqKey="Fang W" first="Wai-Chi" last="Fang">Wai-Chi Fang</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000B20 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000B20 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= OcrV1 |flux= Main |étape= Exploration |type= RBID |clé= PMC:2426746 |texte= Bio-Inspired Microsystem for Robust Genetic Assay Recognition }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:18566679" \ | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \ | NlmPubMed2Wicri -a OcrV1
![]() | This area was generated with Dilib version V0.6.32. | ![]() |