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courses:be5b33prg:homeworks:protein_folding [2015/11/23 09:53]
xposik [Bonus task: Protein folding]
courses:be5b33prg:homeworks:protein_folding [2015/11/23 09:57]
xposik [Suggestions for elaboration]
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 ===== Data ===== ===== Data =====
  
-We provide a {{courses:a4b99rph:cviceni:​testsuite.txt|dataset with various amino acids sequences}} to be folded into minimal energy configurations. This dataset will also be used for the task evaluation.+We provide a {{:courses:be5b33prg:homeworks:​testsuite.txt|dataset with various amino acids sequences}} to be folded into minimal energy configurations. This dataset will also be used for the task evaluation.
  
  
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 First and utmost, read the specs carefully and make sure you understand them. First and utmost, read the specs carefully and make sure you understand them.
  
-  * Decide what formalism you will use. Implement a vector class for representation of amino acid sequences and configurations,​ which also allows to compute the cumulative sum of the vector (to compute the positions based on configuration),​ the elementwise multiplication (for folding), and computation of the free energy. You can use the formalism chosen for module ''​folding'',​ or you can choose a different one. Module ''​folding''​ is implemented in pure Python; maybe using ''​numpy''​ library would be better.+  * Decide what formalism you will use. Implement a vector class for representation of amino acid sequences and configurations,​ which also allows to compute the cumulative sum of the vector (to compute the positions based on configuration),​ the elementwise multiplication (for folding), and computation of the free energy. You can use the formalism chosen for module ''​folding'',​ or you can choose a different one. Module ''​folding''​ is implemented in pure Python; maybe using ''​[[http://​www.numpy.org/​|numpy]]''​ library would be better ​(not part of Python standard library, must be installed separately).
  
-  * Your solver (maybe ​a function ​named ''​solve(a)''​) shall take a sequence ​of amino acids as its input, ​and shall provide ​configuration ''​c''​ (sequence ​of length ''​len(a)-1''​) representing the final configuration of protein. You should make sure that the resulting configuration is self-avoiding,​ i.e. when positions of amino acids are computed based on the configuration,​ no position is attended twice or more times.+  * It is highly desirable to create a visualization tool which would display your protein configurations graphically. It may be e.g. a function ''​visualize(a,c)'' ​taking the amino acid sequence and the configuration ​as arguments. Consider using e.g. the ''​[[http://​matplotlib.org|matplotlib]]'' ​plotting library ​(not part of Python standard library, must be installed separately).
  
-  * It is highly desirable to create a visualization tool which would display your protein configurations graphically. It may be e.g. a function ''​visualize(a,​c)'' ​taking ​the amino acid sequence and the configuration ​as arguments.+  * Your solver (maybe ​a function ​named ''​solve(a)''​) shall take a sequence of amino acids as its inputand shall provide configuration ''​c''​ (sequence of length ''​len(a)-1''​) representing ​the final configuration of protein. You should make sure that the resulting configuration is self-avoiding,​ i.e. when positions of amino acids are computed based on the configuration, no position is attended twice or more times.
  
  
courses/be5b33prg/homeworks/protein_folding.txt · Last modified: 2015/11/23 09:57 by xposik