@article{(Open Science Index):https://publications.waset.org/pdf/10002953,
	  title     = {Noninvasive Disease Diagnosis through Breath Analysis Using DNA-Functionalized SWNT Sensor Array},
	  author    = {Wenjun Zhang and  Yunqing Du and  Ming L. Wang},
	  country	= {},
	  institution	= {},
	  abstract     = {Noninvasive diagnostics of diseases via breath
analysis has attracted considerable scientific and clinical interest for
many years and become more and more promising with the rapid
advancements in nanotechnology and biotechnology. The volatile
organic compounds (VOCs) in exhaled breath, which are mainly
blood borne, particularly provide highly valuable information about
individuals’ physiological and pathophysiological conditions.
Additionally, breath analysis is noninvasive, real-time, painless, and
agreeable to patients. We have developed a wireless sensor array
based on single-stranded DNA (ssDNA)-functionalized single-walled
carbon nanotubes (SWNT) for the detection of a number of
physiological indicators in breath. Seven DNA sequences were used
to functionalize SWNT sensors to detect trace amount of methanol,
benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol,
which are indicators of heavy smoking, excessive drinking, and
diseases such as lung cancer, breast cancer, and diabetes. Our test
results indicated that DNA functionalized SWNT sensors exhibit
great selectivity, sensitivity, and repeatability; and different
molecules can be distinguished through pattern recognition enabled
by this sensor array. Furthermore, the experimental sensing results
are consistent with the Molecular Dynamics simulated ssDNAmolecular
target interaction rankings. Thus, the DNA-SWNT sensor
array has great potential to be applied in chemical or biomolecular
detection for the noninvasive diagnostics of diseases and personal
health monitoring.
	    journal   = {International Journal of Biotechnology and Bioengineering},
	  volume    = {9},
	  number    = {12},
	  year      = {2015},
	  pages     = {818 - 821},
	  ee        = {https://publications.waset.org/pdf/10002953},
	  url   	= {https://publications.waset.org/vol/108},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 108, 2015},