Computationele Biochemie - Bewerkingsoverzicht

R0984908: /* 22/06/2026 VM */

2026-06-22T08:47:55Z

22/06/2026 VM

← Oudere versie		Versie van 22 jun 2026 10:47
Regel 9:		Regel 9:
	==Examenvragen==		==Examenvragen==
	===22/06/2026 VM===		===22/06/2026 VM===
	# Write a function that: takes a 2D-NumPy array, checks if it is a 2D-NumPy array and returns a dictionary with the width, height, array-mean, array-max & array-min.		# Write a function that: takes a 2D-NumPy array, checks if it is a 2D-NumPy array and returns a dictionary with the width, height, array-mean, array-max & array-min. NumPy functions werden gegeven
	NumPy functions gegeven
	# Algorithmic Understanding: code gegeven:		# Algorithmic Understanding: code gegeven:
	## def parse_pdbca_only(file_path)		## def parse_pdbca_only(file_path)
Regel 19:		Regel 18:
	## Welke atomen vormen psi? Welke vormen phi?		## Welke atomen vormen psi? Welke vormen phi?
	## Interperteer jouw resultaten.		## Interperteer jouw resultaten.

	===19/06/2026 NM===		===19/06/2026 NM===
	#Write a function plot_analytical_solution() that: takes rate constant k and initial concentration [A]0 as parameters, uses np.linspace to create time points (e.g., 0 to 10 seconds), calculates [A](t) over time, plots the concentration profile, includes proper axis labels.		#Write a function plot_analytical_solution() that: takes rate constant k and initial concentration [A]0 as parameters, uses np.linspace to create time points (e.g., 0 to 10 seconds), calculates [A](t) over time, plots the concentration profile, includes proper axis labels.

R0984908: /* Examenvragen */

2026-06-22T08:46:25Z

Examenvragen

← Oudere versie		Versie van 22 jun 2026 10:46
Regel 12:		Regel 12:
	NumPy functions gegeven		NumPy functions gegeven
	# Algorithmic Understanding: code gegeven:		# Algorithmic Understanding: code gegeven:
	def parse_pdbca_only(file_path)		## def parse_pdbca_only(file_path)
	def make_distance_matrix(ca_coords)		##def make_distance_matrix(ca_coords)
	## Wat is een PDB-file? Wat doet parse_pdb_ca_only, wat doet make_distance_matrix? Wat is de relatie tussen deze functies? Wat is een distance matrix? Wat is het verschil met een contactmap? Interpreteer het patroon van de distance matrix.		## Wat is een PDB-file? Wat doet parse_pdb_ca_only, wat doet make_distance_matrix? Wat is de relatie tussen deze functies? Wat is een distance matrix? Wat is het verschil met een contactmap? Interpreteer het patroon van de distance matrix.
	# Group Project: GP3		# Group Project: GP3

R0984908: /* Examenvragen */

2026-06-22T08:45:58Z

Examenvragen

@@ Regel 8: / Regel 8: @@
 ==Examenvragen==
 ===19/06/2026 NM===
-#Write a function plot_analytical_solution() that: takes rate constant k and initial concentration [A]0 as parameters, uses np.linspace to create time points (e.g., 0 to 10 seconds), calculates
+#Write a function plot_analytical_solution() that: takes rate constant k and initial concentration [A]0 as parameters, uses np.linspace to create time points (e.g., 0 to 10 seconds), calculates [A](t) over time, plots the concentration profile, includes proper axis labels.
 Functies plt.show() plt.xlabel(), plt.ylabel(), plt.legend() ... allemaal gegeven, np.linspace(min, max, num) en np.exp() ook
 #Algorythmic Understanding: code gegeven over convolution kernel met afbeelding vanonder (eerst afbeelding [7,7] met value 0(zwart), daarin [2:5, 2:5] met value 1(wit), tweede afbeelding is met convolution dus de overgang van zwart naar wit gaat via grijstinten)

R0976654: /* Vakinformatie */

2026-06-20T13:39:29Z

Vakinformatie

← Oudere versie		Versie van 20 jun 2026 15:39
Regel 1:		Regel 1:
	[[Categorie:Bachelor Biochemie]]		[[Categorie:Bachelor Biochemie]]
	==Vakinformatie==		==Vakinformatie==
	Mondeling examen met schriftelijke voorbereiding bij Xin en Peter Dedecker. Xin neemt het examen af, Dedecker zit erbij voor eventuele vertaling naar het Engels. Als Dedecker er niet kan zijn, zit er iemand anders om te vertalen.		Mondeling examen met schriftelijke voorbereiding bij Xin en Peter Dedecker. Xin neemt het examen af, Dedecker zit erbij voor eventuele vertaling naar het Engels maar hij kan ook nog bijvragen stellen. Als Dedecker er niet kan zijn, zit er iemand anders om te vertalen.
	Alle vragen staan zowel in het Nederlands als het Engels en je mag kiezen in welke taal je antwoordt, maar Engels is handiger om in gesprek te gaan met Xin.		Alle vragen staan zowel in het Nederlands als het Engels en je mag kiezen in welke taal je antwoordt, maar Engels is handiger om in gesprek te gaan met Xin.
	Je krijgt 3 vragen: de eerste vraag is coderen. Hiervoor krijg je een aantal functies die je kan gebruiken.		Je krijgt 3 vragen: de eerste vraag is coderen. Hiervoor krijg je een aantal functies die je kan gebruiken.

R0976654: /* Vakinformatie */

2026-06-20T13:39:06Z

Vakinformatie

← Oudere versie		Versie van 20 jun 2026 15:39
Regel 1:		Regel 1:
	[[Categorie:Bachelor Biochemie]]		[[Categorie:Bachelor Biochemie]]
	==Vakinformatie==		==Vakinformatie==
	~~Nieuw vak vanaf 2025-2026~~.		Mondeling examen met schriftelijke voorbereiding bij Xin en Peter Dedecker. Xin neemt het examen af, Dedecker zit erbij voor eventuele vertaling naar het Engels. Als Dedecker er niet kan zijn, zit er iemand anders om te vertalen.
			Alle vragen staan zowel in het Nederlands als het Engels en je mag kiezen in welke taal je antwoordt, maar Engels is handiger om in gesprek te gaan met Xin.
			Je krijgt 3 vragen: de eerste vraag is coderen. Hiervoor krijg je een aantal functies die je kan gebruiken.
			De tweede vraag gaat over 1 van de assignments. Hierbij krijg je ook een deel code en moet je daar vragen over beantwoorden.
			De derde vraag gaat over je groepswerk. Er zijn ongeveer 5 bijvragen hier.

	==Examenvragen==		==Examenvragen==
	===19/06/2026 NM===		===19/06/2026 NM===

R0976654: /* Examenvragen */

2026-06-20T13:26:29Z

Examenvragen

@@ Regel 3: / Regel 3: @@
 Nieuw vak vanaf 2025-2026.
 ==Examenvragen==
 ===8/06/2026 (VM)===
-#Kleine problem set (zelf code schrijven): Hamming Distance
+#Kleine probleem set (zelf code schrijven): Hamming Distance
 #Big problem set (Code gegeven en vragen erover beantwoorden): Manhattan Tourist Problem using Top-Down dynamics with memoization and path traceback
 ##Explain the role of 'self.memo' (explain what information is stored in 'self.memo', why the keys are tuples such as (i,j), and how this changes the efficiency of the recursive solution.

R0986024: /* Examenvragen */

2026-06-08T14:22:20Z

Examenvragen

← Oudere versie		Versie van 8 jun 2026 16:22
Regel 18:		Regel 18:
	#Groups project		#Groups project
	#:*GP3 (raw and minimised torsion angle comparison)		#:*GP3 (raw and minimised torsion angle comparison)
	##:Explain Ramachandran and Janin plot		##Explain Ramachandran and Janin plot
	#:::*Wat is put on which axis		#:::*Wat is put on which axis
	#:::*What is the difference between them		#:::*What is the difference between them
Regel 26:		Regel 26:
	#:::*W what do v1, v2, v3, n1 and n2 represent		#:::*W what do v1, v2, v3, n1 and n2 represent
	#:::*What makes up a "vlak"		#:::*What makes up a "vlak"
	##:*Given 3 Ramachandran plots (raw, minimised and overlay)		##Given 3 Ramachandran plots (raw, minimised and overlay)
	#:::*Do these plots represent 1 protein or a protein set?		#:::*Do these plots represent 1 protein or a protein set?
	#:::*When would we use these plots? What are they used for?		#:::*When would we use these plots? What are they used for?

R0986024: /* 8/06/2026 (VM) */

2026-06-08T14:21:43Z

8/06/2026 (VM)

← Oudere versie		Versie van 8 jun 2026 16:21
Regel 12:		Regel 12:
	#:::* what kind of information stores 'self.memo' (possibilities: string, ...)		#:::* what kind of information stores 'self.memo' (possibilities: string, ...)
	##Identify the base cases and the recursive cases in 'MTP(i,j)', and explain why they are necessary (distinguish clearly between the starting condition of the recursion, the condition that prevents the algorithm from leaving the grid and the part that reduces the problem to smaller subproblems)		##Identify the base cases and the recursive cases in 'MTP(i,j)', and explain why they are necessary (distinguish clearly between the starting condition of the recursion, the condition that prevents the algorithm from leaving the grid and the part that reduces the problem to smaller subproblems)
	#:: Bijvragen:		#::Bijvragen:
	#:::* Why -1 and not 0 (for the part that prevents the algorithm from leaving the grid)		#:::*Why -1 and not 0 (for the part that prevents the algorithm from leaving the grid)
	##Explain how the algorithm finds not only the optimal score but also the optimal path. (Describe the roles of 'up', 'left', ' diagonal', 'self.path', and 'get.path()'. The answer should make clear why the following stored predecessors reconstruct an optimal path.		##Explain how the algorithm finds not only the optimal score but also the optimal path. (Describe the roles of 'up', 'left', ' diagonal', 'self.path', and 'get.path()'. The answer should make clear why the following stored predecessors reconstruct an optimal path.
	#:: Bijvragen:		#::Bijvragen:
	#Groups project		#Groups project
	#:* GP3 (raw and minimised torsion angle comparison)		#:*GP3 (raw and minimised torsion angle comparison)
	##: Explain Ramachandran and Janin plot		##:Explain Ramachandran and Janin plot
	#:::* ~~what~~ is put on which axis		#:::*Wat is put on which axis
	#:::* ~~what~~ is the difference between them		#:::*What is the difference between them
	## Give the atoms that define phi and psi		##Give the atoms that define phi and psi
	## Where in the plot is the beta-sheet and why		##Where in the plot is the beta-sheet and why
	## Explain the given code (here, the code was the one from the dehidral angle)		##Explain the given code (here, the code was the one from the dehidral angle)
	#:::* what do v1, v2, v3, n1 and n2 represent		#:::*W what do v1, v2, v3, n1 and n2 represent
	#:::* ~~what~~ makes up a "vlak"		#:::*What makes up a "vlak"
	##:* ~~given~~ 3 Ramachandran plots (raw, minimised and overlay)		##:*Given 3 Ramachandran plots (raw, minimised and overlay)
	#:::* Do these plots represent 1 protein or a protein set?		#:::*Do these plots represent 1 protein or a protein set?
	#:::* When would we use these plots? What are they used for?		#:::*When would we use these plots? What are they used for?

R0986024: /* 8/06/2026 (VM) */

2026-06-08T14:20:05Z

8/06/2026 (VM)

← Oudere versie		Versie van 8 jun 2026 16:20
Regel 18:		Regel 18:
	#Groups project		#Groups project
	#:* GP3 (raw and minimised torsion angle comparison)		#:* GP3 (raw and minimised torsion angle comparison)
	##:* explain Ramachandran and Janin plot		##: Explain Ramachandran and Janin plot
	#:::* what is put on which axis		#:::* what is put on which axis
	#:::* what is the difference between them		#:::* what is the difference between them
	##~~:* give~~ the atoms that define phi and psi		## Give the atoms that define phi and psi
	##~~:* where~~ in the plot is the beta-sheet and why		## Where in the plot is the beta-sheet and why
	##~~:* explain~~ the given code (here, the code was the one from the dehidral angle)		## Explain the given code (here, the code was the one from the dehidral angle)
	#:::* what do v1, v2, v3, n1 and n2 represent		#:::* what do v1, v2, v3, n1 and n2 represent
	#:::* what makes up a "vlak"		#:::* what makes up a "vlak"

R0986024: /* 8/06/2026 (VM) */

2026-06-08T14:18:18Z

8/06/2026 (VM)

← Oudere versie		Versie van 8 jun 2026 16:18
Regel 6:		Regel 6:
	#Kleine problem set (zelf code schrijven): Hamming Distance		#Kleine problem set (zelf code schrijven): Hamming Distance
	#Big problem set (Code gegeven en vragen erover beantwoorden): Manhattan Tourist Problem using Top-Down dynamics with memoization and path traceback		#Big problem set (Code gegeven en vragen erover beantwoorden): Manhattan Tourist Problem using Top-Down dynamics with memoization and path traceback
	##:Explain the role of 'self.memo' (explain what information is stored in 'self.memo', why the keys are tuples such as (i,j), and how this changes the efficiency of the recursive solution.		##Explain the role of 'self.memo' (explain what information is stored in 'self.memo', why the keys are tuples such as (i,j), and how this changes the efficiency of the recursive solution.
	#:: Bijvragen:		#:: Bijvragen:
	#:::* what would happen if we remove 'self.memo'		#:::* what would happen if we remove 'self.memo'
	#:::* What is 'self.memo'?		#:::* What is 'self.memo'?
	#:::* what kind of information stores 'self.memo' (possibilities: string, ...)		#:::* what kind of information stores 'self.memo' (possibilities: string, ...)
	##:Identify the base cases and the recursive cases in 'MTP(i,j)', and explain why they are necessary (distinguish clearly between the starting condition of the recursion, the condition that prevents the algorithm from leaving the grid and the part that reduces the problem to smaller subproblems)		##Identify the base cases and the recursive cases in 'MTP(i,j)', and explain why they are necessary (distinguish clearly between the starting condition of the recursion, the condition that prevents the algorithm from leaving the grid and the part that reduces the problem to smaller subproblems)
	#:: Bijvragen:		#:: Bijvragen:
	#:::* Why -1 and not 0 (for the part that prevents the algorithm from leaving the grid)		#:::* Why -1 and not 0 (for the part that prevents the algorithm from leaving the grid)
	##:Explain how the algorithm finds not only the optimal score but also the optimal path. (Describe the roles of 'up', 'left', ' diagonal', 'self.path', and 'get.path()'. The answer should make clear why the following stored predecessors reconstruct an optimal path.		##Explain how the algorithm finds not only the optimal score but also the optimal path. (Describe the roles of 'up', 'left', ' diagonal', 'self.path', and 'get.path()'. The answer should make clear why the following stored predecessors reconstruct an optimal path.
	#:: Bijvragen:		#:: Bijvragen:
	#Groups project		#Groups project