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predict clinical outcome based on the chosen features. Computational diagnostics
includes identifi cation of novel, molecularly defi ned entities of a disease. For many
clinical decision problems where a large number of features are used to monitor a
disease, neural networks and other machine-learning approaches can help to manage
the situation.
The impact of having the human sequence and personalized digital images in
hand has also created tremendous demands of developing powerful supercomput-
ing, statistical learning and artifi cial intelligence approaches to handle the massive
bioinformatics and personalized healthcare data, which will obviously have a pro-
found effect on how biomedical research will be conducted toward the improve-
ment of human health and prolonging of human life in the future. The International
Society of Intelligent Biological Medicine ( http://www.isibm.org ) touches future
bioinformatics and personalized medicine throughout current efforts in promoting
the research, education and awareness of the upcoming integrated inter/multidisci-
plinary fi eld (Yang et al. 2008 ).
Wireless non-invasive biosensors are in development for monitoring of all vital
signs including continuous blood pressure, heart rhythm, oximetry, respiratory rate,
and temperature. A subcutaneous sensor can provide a highly accurate reading of
glucose every 5 min for continuous glucose monitoring of diabetics. A cell-phone-
sized device can be used to acquire high-resolution 2D echocardiography and color
fl ow. Consumers will soon learn how to acquire their own echocardiograms, fetal
ultrasounds, or breast ultrasounds, and transmit the images for their physicians for
real-time interpretation. Along with genomic information, digital technologies will
facilitate the practice of personalized medicine.
Exploration of Disease-Gene Relationship
LARaLink 2.0 (Loci Analysis for Rearrangement Link) is an enabling web technol-
ogy that permits the rapid retrieval of clinical cytogenetic and molecular data. New
data mining capabilities have been incorporated into version 2.0, building upon
LARaLink 1.0, to extend the utility of the system for applications in both the clini-
cal and basic sciences. These include access to the Chromosomal Variation in Man
database and the GEO database. Together these new resources enhance the user’s
ability to associate genotype with phenotype to identify potential gene candidates.
Unlimited access for researchers exploring disease-gene relationships and for clini-
cians extending practice in patient care is available online (LARaLink.bioinformat-
ics.wayne.edu:8080/unigene).
Biosimulation Techniques for Developing Personalized Medicine
An example of this is REFS™ (Reverse Engineering and Forward Simulation) tech-
nology used by Gene Network Sciences Inc in pharmaceutical and clinical settings to
rapidly turn combinations of genetic, genomic, and clinical measurements into mod-
20 Development of Personalized Medicine