Title :
Robust Bioinformatics Recognition with VLSI Biochip Microsystem
Author :
Lue, Jaw-Chyng L. ; Fang, Wai-Chi
Author_Institution :
Dept. of Electr. Eng., Southern California Univ., Los Angeles, CA
Abstract :
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR) amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized
Keywords :
DNA; VLSI; bioMEMS; biomedical optical imaging; fluorescence; lab-on-a-chip; learning (artificial intelligence); medical image processing; molecular biophysics; neural nets; pattern recognition; VLSI biochip microsystem; artificial neural network learning algorithm; differential logarithmic imaging chip; error backpropagation algorithm; fluorescence patterns; on-chip DNA analysis; polymerase chain reaction amplification; robust bioinformatics patterns recognition; sigmoid-logarithmic transfer function; single-rail logarithmic circuit; Artificial neural networks; Backpropagation algorithms; Bioinformatics; DNA; Fluorescence; Pattern analysis; Pattern recognition; Robustness; System-on-a-chip; Very large scale integration;
Conference_Titel :
Life Science Systems and Applications Workshop, 2006. IEEE/NLM
Conference_Location :
Bethesda, MD
Print_ISBN :
1-4244-0277-8
Electronic_ISBN :
1-4244-0278-6
DOI :
10.1109/LSSA.2006.250384