Bio-inspired microsystem for robust genetic assay recognition

Jaw Chyng Lue*, Wai-Chi Fang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 differential logarithm stage 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 winner-take-all (WTA) function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the error backpropagation (BP) algorithm is proposed for robustly recognizing low intensity patterns. Our results show the trained new ANN can recognize low fluorescence patterns better than the ANN using the conventional sigmoid function.

Original languageEnglish
Title of host publicationProceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007
Pages572-577
Number of pages6
DOIs
StatePublished - 1 Dec 2007
EventFrontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007 - Jeju Island, Korea, Republic of
Duration: 11 Oct 200713 Oct 2007

Publication series

NameProceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007

Conference

ConferenceFrontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007
CountryKorea, Republic of
CityJeju Island
Period11/10/0713/10/07

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