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well as to be able to identify the circumstances,
where such tools could be helpful, and might deliver
intelligent and educated conclusions, even more than
expert human physicians (Korhonen et al., 2009).
Another important goal is to provide physicians the
basic skills required to implement, tune and even
participate in the development process of such tools.
The course is built as a dialog between horizontal
and vertical subjects, being the medical applications
of data mining algorithms, on one hand, and the
computational methodologies that are intertwined in
each of those applications, on the other hand. The
topics regarding medical applications are: the
automatic collection and management of medical
data, information and knowledge; the semantic
analysis of text, the individual-based vs. the
population-based analysis of EMRs; the 4-dimension
visualization of biological phenomena based on even
sparse pieces of partial knowledge; the prediction of
treatment outcome; the decentralization of medical
assessment and treatment using telemedicine aided
encounters; and the overall movement towards an
era of a much more personalized medicine, which is
based, among other types of clinical data, on the
patient’s own genome.
The other axis of topics - the computational
methodologies, is comprised of the fundamental
theories of computation and data mining, as well as
basic algorithms in this field. The ones we found as
most relevant are: data representation options,
information retrieval (IR) engines, pattern
recognition, motif discovery, clustering, classifiers,
machine learning, multi-dimensional search,
decision trees and basic graph theory. In addition to
the theoretic lectures, we hold hands-on exercise
sessions, in which we teach the SQL language and
the ‘Weka 3’ data mining suite.
Two additional special chapters are dedicated to
smartphone apps for physicians, such as:
‘ePocrates’, ‘AOTrauma’ and ‘Calculate’; and to
medicine-oriented social networks and web services,
such as: ‘Patients Like Me’, ‘23andMe’ and
‘Knome’. Since these two topics can be considered
as somewhat more “stand alone”, not tightly
connected to the other more classic data mining
topics, they are taught in the framework of special
seminar. Most of the seminar is built around real-life
examples. They are demonstrated and discussed by a
practicing physician, who uses such applications in
his day-to-day work. In addition to our students, we
invite to this special seminar other Israeli
researchers, physicians and managers from the
medical domain, who still do not practice
biomedical informatics. We do that in order to
harbour these easily explained yet impressive topics
as an introduction to the field and our study program
and encourage enrolment for the following year.
6 DISCUSSION
Computational Biology is a result of the marriage of
Computer Science and Biology. Now that
computational biology has come of age, the time is
ripe for the next step of integrating computational
biology with medicine. Clearly, there are many
considerations when starting such a program and
many compromises and adjustments have to be
made in order to fit the program to the needs of the
students. One of the problems we encountered is the
diverse background and interest of the students, thus,
it was not simple to come up with a program that
would appeal to all students.
The feedback we received from the participants of
the first year of the program was very encouraging.
All students mentioned that the program opened their
eyes to the new world of research and treatment
opportunities. However, we could see again the
diversity among our students. While some of the
students wanted the program to be more hands-on and
practical, others actually suggested concentrating
more on theoretical issues. While some said they
preferred to get a stronger mathematical and
computational basis (including programming), other
students complained that this material was already
excessive and too difficult for them.
For us it was amazing to see how quickly the
program paid off. One of the students, a children
neurologist, told us that being inspired by the
Systems Biology course, she changed the treatment
of one of her patients. It is a patient who suffered
from the rare Ruvalcabra syndrome, which is caused
by mutations in the PTEN gene. The patient was
treated for seizures and behavioural problems
without much success. Led by insights she gained
from the course, she tried off-label treatment with
Rapamune, a drug that is often prescribed for
Tuberous Sclerosis, which is another syndrome that
shares the same pathway with Ruvalcabra.
Surprisingly, the patient showed a significant
cognitive improvement. While additional research is
needed to follow up this and other patients, it is clear
that the program already inspired clinical innovation.
A lot of research and collaborative thinking were
put together in this initiative. Our hopes are that
other institutes in Israel and around the world will
follow with similar programs, and that together we
will influence the building of the future cadre of
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