A F I R S T COUR S E IN
SYSTEMS
BIOLOGY
SOLUTIONS TO EXERCISES
THIRD
EDITION
Eberhard O. Voit, Melissa K. Kemp,
Po-Wei Chen, I-Chun Chou, Sepideh Dolatshahi,
Luis Fonseca, James Kelvin, Yun Lee, Zhen Qi,
Andrew Sedler, and Weiwei Yin
Atlanta & Dallas, 2024
,
,PREAMBLE TO SOLUTIONS
Most exercises in A First Course in Systems Biology are structured to be open-ended
and stimulate self-motivated learning and exploration. As a consequence, they do
not have unique solutions. Some students find this ambiguity uncomfortable and
would much rather be assured that there is one correct solution. However, after a
while, they often see that open-ended questions are much closer to reality, espe-
cially with respect to complex phenomena in biology. Furthermore, the students
recognize that they can structure their solutions, to some degree, according to
their own preference: some students like conceptual approaches, others like simu-
lations, yet others are intrigued by rigorous proofs. Some enjoy trying out multiple
changes in model settings and studying the responses of a system; others would
much rather extract the essence of a problem and try to solve it as concisely as pos-
sible, while some prefer to spend their time screening the literature for experts’
answers or solutions to similar problems. Many students have asked us: how many
simulations do I have to do? Initially, they sometimes do not like my answer:
“Before you execute a simulation, make a prediction of what you expect to happen.
If your predictions are consistently correct, at least qualitatively, you may stop.
However, if your predictions are sometimes correct and sometimes false, there are
aspects of the system you don’t really understand. You need to keep on simulating,
analyzing, and interpreting.”
Many exercises permit a lot of latitude in terms of breadth and depth, and the
instructor might want to specify the expected length of a report, the level of detail
of an analysis, and possibly a specific focus. For instance, if students are asked to
explore different visualizations of protein structures in the protein data bank PDB,
one could ask them to focus on specific proteins that, for some reason, are of par-
ticular interest to the student, class, or the program. Some exercises ask for reports
excerpting information from the literature or the Internet. The answers proposed
here usually do not offer as much detail as one might expect from a student, but
merely point to relevant information and highlight important topics. The instruc-
tor also needs to decide how to handle the issue of artificial intelligence as a tool
for generating solutions. Similarly, the exploration of software requires working
hands-on with the program, and the solutions just provide pointers as to where
and how to start. Again, it might be useful to connect these software questions with
a specific biological question.
The total number of exercises per chapter is probably too high for a typical one-
semester class but affords the instructor some flexibility in choosing exercises that
are deemed most relevant for the types of students taking the class, their back-
grounds in biology, mathematics, and computing, and the department or program
in which the course is taught. Finally, the large number and variety of exercises,
and the in-built flexibility in solution strategies, suggest that some of the proposed
solutions could probably be improved. We would be very happy to receive better
solutions and possibly include them in future versions of this solution manual.
,
SYSTEMS
BIOLOGY
SOLUTIONS TO EXERCISES
THIRD
EDITION
Eberhard O. Voit, Melissa K. Kemp,
Po-Wei Chen, I-Chun Chou, Sepideh Dolatshahi,
Luis Fonseca, James Kelvin, Yun Lee, Zhen Qi,
Andrew Sedler, and Weiwei Yin
Atlanta & Dallas, 2024
,
,PREAMBLE TO SOLUTIONS
Most exercises in A First Course in Systems Biology are structured to be open-ended
and stimulate self-motivated learning and exploration. As a consequence, they do
not have unique solutions. Some students find this ambiguity uncomfortable and
would much rather be assured that there is one correct solution. However, after a
while, they often see that open-ended questions are much closer to reality, espe-
cially with respect to complex phenomena in biology. Furthermore, the students
recognize that they can structure their solutions, to some degree, according to
their own preference: some students like conceptual approaches, others like simu-
lations, yet others are intrigued by rigorous proofs. Some enjoy trying out multiple
changes in model settings and studying the responses of a system; others would
much rather extract the essence of a problem and try to solve it as concisely as pos-
sible, while some prefer to spend their time screening the literature for experts’
answers or solutions to similar problems. Many students have asked us: how many
simulations do I have to do? Initially, they sometimes do not like my answer:
“Before you execute a simulation, make a prediction of what you expect to happen.
If your predictions are consistently correct, at least qualitatively, you may stop.
However, if your predictions are sometimes correct and sometimes false, there are
aspects of the system you don’t really understand. You need to keep on simulating,
analyzing, and interpreting.”
Many exercises permit a lot of latitude in terms of breadth and depth, and the
instructor might want to specify the expected length of a report, the level of detail
of an analysis, and possibly a specific focus. For instance, if students are asked to
explore different visualizations of protein structures in the protein data bank PDB,
one could ask them to focus on specific proteins that, for some reason, are of par-
ticular interest to the student, class, or the program. Some exercises ask for reports
excerpting information from the literature or the Internet. The answers proposed
here usually do not offer as much detail as one might expect from a student, but
merely point to relevant information and highlight important topics. The instruc-
tor also needs to decide how to handle the issue of artificial intelligence as a tool
for generating solutions. Similarly, the exploration of software requires working
hands-on with the program, and the solutions just provide pointers as to where
and how to start. Again, it might be useful to connect these software questions with
a specific biological question.
The total number of exercises per chapter is probably too high for a typical one-
semester class but affords the instructor some flexibility in choosing exercises that
are deemed most relevant for the types of students taking the class, their back-
grounds in biology, mathematics, and computing, and the department or program
in which the course is taught. Finally, the large number and variety of exercises,
and the in-built flexibility in solution strategies, suggest that some of the proposed
solutions could probably be improved. We would be very happy to receive better
solutions and possibly include them in future versions of this solution manual.
,
