Big Data and Biological Networks Quiz 1: 23 February 2025 (January 2025 term)

1. A

   Peptide bond

2. B

   Glycosidic bond

3. C

   Phosphodiester bond

4. D

   Amide bond

1. A

   DNA gets converted to chromosomes

2. B

   RNA gets converted to protein

3. C

   Protein folding occurs to produce functional enzymes

4. D

   Cells produce ATP

1. A

   Genomics data is independent of the cell type

2. B

   Transcriptomics data is dependent on a specific cell type

3. C

   Both genomics data is independent of the cell type and transcriptomics data is dependent on a specific cell type are true

4. D

   None of these statements are true

1. A

   Longer read lengths.

2. B

   Higher accuracy.

3. C

   Higher throughput.

4. D

   Lower cost per base.

1. A

   Short fragments of DNA created before transcription

2. B

   Byproducts of histone modifications

3. C

   Short fragments of DNA created during replication on the 5’ to 3’ template strand

4. D

   Short fragments of DNA created during replication on the 3’ to 5’ template strand

1. A

   DNA polymerase

2. B

   Sigma factor

3. C

   Uracilase

4. D

   Ribonuclease

Select all that apply.

1. A

   DNA methylation

2. B

   Chromatin accessibility

3. C

   Genome wide association studies

4. D

   Differential expression analysis

Select all that apply.

1. A

   A - 2, B - 1, C - 4, D - 3

2. B

   A - 4, B - 2, C - 1, D - 3

3. C

   A - 3, B - 2, C - 1, D - 3

4. D

   A - 3, B - 2, C - 1, D - 4

Select all that apply.

1. A

   Both the assertion and reason are correct, and the reason is a correct explanation of the assertion.

2. B

   Both the assertion and reason are correct, but the reason is not a correct explanation of the assertion.

3. C

   The assertion is correct, but the reason is incorrect.

4. D

   The assertion is incorrect, but the reason is correct.

Select all that apply.

1. A

   Transcription uses two strands of DNA

2. B

   Polyadenylation does not happen in prokaryotic cells

3. C

   Intronic genes are only present in eukaryotic cells

4. D

   Proteins are produced in the nuclei

Select all that apply.

1. A

   Identifying individuals based on DNA evidence

2. B

   Tracking the spread of infectious diseases

3. C

   Predictive testing for genetic diseases

4. D

   Identifying genetic diversity within species

1. A

   0.67

2. B

   0.50

3. C

   0.31

4. D

   0.44

1. A

   1/3

2. B

   4/3

3. C

   8/3

4. D

   2/3

1import networkx as nx
2
3G = nx.DiGraph()
4G.add_edges_from([(1, 2), (2, 3), (3, 4)])
5
6H = nx.Graph(G)
7
8G.add_edge(4, 1)
9print(list(H.neighbors(1)))

1. A

   AttributeError: 'Graph' object has no attribute 'add_edge'

2. B

   TypeError: 'DiGraph' object is not subscriptable

3. C

   NetworkXError: Graph is immutable

4. D

   [2]

1. A

2. B

3. C

4. D

Select all that apply.

1. A

   In a bipartite graph, there are two disjoint sets of vertices such that no two vertices within the same set are adjacent.

2. B

   Every complete bipartite graph has an Eulerian circuit.

3. C

   A bipartite graph can be colored with two colors such that no two adjacent nodes have the same color.

4. D

   In the adjacency matrix of a bipartite graph, the values corresponding to edges within the same set of nodes will not all be zero.

Select all that apply.

1. A

   In a small-world network, as the rewiring probability p increases, the average path length decreases dramatically.

2. B

   Random networks tend to have high clustering coefficients compared to small- world networks for small p.

3. C

   In a small-world network, increasing the rewiring probability p makes the network more disconnected and increases the clustering coefficient.

4. D

   Small-world networks have a balance of high clustering and short average path length for intermediate values of rewiring probability p.

Select all that apply.

1. A

   Small-world network because it ensures high clustering, which represents functional metabolic clusters and pathways, while also having short path lengths for efficient chemical signaling.

2. B

   Random network because it randomly connects metabolites and enzymes, ensuring diverse and unpredictable interactions in the network.

3. C

   Power-law network because it produces a few highly connected nodes (hub enzymes) that play crucial roles in regulating key metabolic pathways.

4. D

   Random network because it results in efficient information transfer through a uniform distribution of connections between metabolites and enzymes.

1. A

   0.429

2. B

   0.333

3. C

   0.524

4. D

   0.286

1. A

   0.571

2. B

   0.714

3. C

   0.429

4. D

   0.857

1. A

   0.464

2. B

   0.393

3. C

   0.500

4. D

   0.429

1. A

   0.538

2. B

   0.636

3. C

   0.583

4. D

   0.500