Home / Study library / Big Data and Biological Networks / End Term · Jan 2024 Big Data and Biological Networks · End Term · Jan 2024 · FN
Big Data and Biological Networks · End Term · Jan 2024 FN
← Course papers · Start practice / exam
Questions and published explanations below are available without starting a test. Some questions may not have a published solution yet.
0 / 42 published solutions
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33 Q34 Q35 Q36 Q37 Q38 Q39 Q40 Q41 Q42 Q43 Question 2 MSQ · 3.0 marks In the graph shown below
6406532754544. There is an Eulerian path starting from the node "a"
6406532754545. There is an Eulerian cycle starting from the node "a"
6406532754546. There are Eulerian paths from all the nodes
6406532754547. There are no Eulerian cycles
A published solution is not available for this question yet.
Report a correction for Q2
Question 3 MSQ · 3.0 marks Assume you have been provided with well-curated highly accurate constraint-based genome-scale
metabolic models. Which of the following studies can be carried out on the models provided
6406532754548. Metabolic engineering to increase yields of a target metabolite
6406532754549. Temporal evolution of cellular phenotypes
6406532754550. Kinetics of enzyme catalysed reactions
6406532754551. Prediction of interspecies interactions
A published solution is not available for this question yet.
Report a correction for Q3
Question 4 MSQ · 3.0 marks Signal transduction networks have long cascades. What advantages do they provide?
6406532754552. Gives more time for protein synthesis
6406532754553. Long cascades form more efficient modules
6406532754554. Many levels of control to ensure better regulation
6406532754555. Signal amplification from small input to high output of final product(s)
A published solution is not available for this question yet.
Report a correction for Q4
Question 5 MSQ · 3.0 marks The number of stuck/blocked reactions in the microbe ‘A’ when grown alone is 27. The number of
stuck reactions is reduced to 15 when ‘A’ is grown together with ‘B’. Also, when ‘A’ is grown
together with ‘C’, the number of stuck reactions in ‘A’ is 7. Which of the following is/are true?
6406532754556. MSI(A;AUB) = 0.55
6406532754557. MSI(A;AUB) = 0.44
6406532754558. MSI(A;AUC) = 0.74
6406532754559. MSI(A;AUC) = 0.26
A published solution is not available for this question yet.
Report a correction for Q5
Question 6 MCQ · 3.0 marks Consider the given below network and identify the possible gene-regulatory interactions
6406532754560. Gene 3 -> Gene 2
6406532754561. Gene 3 -> Gene 1
6406532754562. Gene 2 -> Gene 1
6406532754563. Gene 2 -> Gene 3
A published solution is not available for this question yet.
Report a correction for Q6
Question 7 MCQ · 3.0 marks Which network model is obtained using the “preferential attachment” method of network growth?
6406532754564. Random network
6406532754565. Power law network
6406532754566. Erdős–Rényi network
6406532754567. Small world network
A published solution is not available for this question yet.
Report a correction for Q7
Question 8 MCQ · 3.0 marks Consider a toy model with 4 reactions, namely R1, R2, R3 and R4. The GPR (gene protein reaction)
rules for each of the reactions are given below:
a) R1 = gene 1 OR gene 2
b) R2 = NOT gene 3
c) R3 = gene 4 AND gene 5
d) R4 = gene 1
If gene 1 and gene 4 are knocked out, which of the reactions mentioned below will be blocked?
A published solution is not available for this question yet.
Report a correction for Q8
Question 9 MCQ · 3.0 marks Based on the phylogenetic profiles given below, indicate which of the following proteins pairs
interact
A published solution is not available for this question yet.
Report a correction for Q9
Question 10 MCQ · 1.0 marks Choose the correct pairs:
6406532754576. Drug-Drug interaction → Multi-label graph classification
6406532754577. Molecule side effect prediction → Graph classification
6406532754578. Protein interface prediction → Node prediction
6406532754579. Drug-Target binding affinity prediction → Graph classification
A published solution is not available for this question yet.
Report a correction for Q10
Question 11 MCQ · 1.0 marks 6406532754580. 6406532754581. 6406532754582. 6406532754583. A published solution is not available for this question yet.
Report a correction for Q11
Question 12 MCQ · 1.0 marks Enumerate the total number of solutions that are possible for a string reconstruction problem
with 21 words?
6406532754584. 6406532754585. 6406532754586. 6406532754587. A published solution is not available for this question yet.
Report a correction for Q12
Question 13 MCQ · 2.0 marks Which of the following statements about GraphSAGE and GAT (Graph Attention Network) is true?
6406532754592. GraphSAGE uses attention mechanisms to aggregate information from
neighboring nodes
6406532754593. GraphSAGE is a node-level representation learning algorithm, while GAT is an
edge-level representation learning algorithm
6406532754594. GAT assigns different importance weights to neighboring nodes during
aggregation based on their relevance to the target node
6406532754595. GraphSAGE is a edge-level representation learning algorithm, while GAT is an
node-level representation learning algorithm
A published solution is not available for this question yet.
Report a correction for Q13
Question 14 MCQ · 2.0 marks Which of the following is true?
6406532754596. Graph pooling refines the node features without changing the graph structure
6406532754597. For node-focused enumerate, a representation of the entire graph is desired
6406532754598. The assignment matrix is used to map super nodes to the original graph
6406532754599. Eigenpooling uses spectral clustering to generate super nodes
A published solution is not available for this question yet.
Report a correction for Q14
Question 15 MCQ · 2.0 marks 6406532754600. 6406532754601. 6406532754602. 6406532754603. A published solution is not available for this question yet.
Report a correction for Q15
Question 16 MCQ · 2.0 marks Why do we need specialized deep learning architectures for graphs?
6406532754604. The flattened adjacency matrix does not change with ordering of nodes
6406532754605. Graphs have variable-sized structures and irregular connectivity patterns
6406532754606. Feed-forward networks are permutation equivariant functions
6406532754607. All of these
A published solution is not available for this question yet.
Report a correction for Q16
Question 17 MCQ · 2.0 marks Given two sequences TATTT and ATAT, in the graph representation of their sequence alignment,
how many nodes are present?
A published solution is not available for this question yet.
Report a correction for Q17
Question 18 MSQ · 2.0 marks In the case of flat graph pooling:
6406532754588. Directly generates a graph-level representation from the node representations
6406532754589. No new graph but a single node being generated
6406532754590. Used for node focused enumerate
6406532754591. Average pooling is a flat graph pooling method
A published solution is not available for this question yet.
Report a correction for Q18
Question 19 MSQ · 2.0 marks Task-specific labels are scarce during the training phase. The pretraining helps to develop a
general understanding of related enumerate with abundant unlabelled data. Then, fine-tuning can
be performed for a downstream task of interest. For the molecular property prediction task, which
of the following are valid pretraining strategies.
6406532754608. Reconstructing the adjacency matrix for each graph using an encoder-decoder
approach
6406532754609. Mask nodes and predict the features of masked nodes during training
6406532754610. Predict the embedding similarity between different graphs
6406532754611. Use subgraphs to predict surrounding graph structures
A published solution is not available for this question yet.
Report a correction for Q19
Question 20 MSQ · 2.0 marks Which of the following are valid regularization approaches for graphs:
6406532754612. Add L1 norm of trainable parameters to supervised loss term
6406532754613. Perturbing node features during training by adding gaussian noise
6406532754614. Force representations of nodes that are not connected to be different
6406532754615. Randomly drop nodes during training
A published solution is not available for this question yet.
Report a correction for Q20
Question 21 MSQ · 2.0 marks Which of the following statements is not true?
6406532754616. Global alignment is more applicable for sequences with similar lengths
6406532754617. Traceback in the score matrix is the only place that the Smith-Waterman
algorithm differs from the Needleman-Wunsch algorithm.
6406532754618. Affine gap penalties are more widely used than constant gap penalties
6406532754619. Sequence alignment cannot be used for identifying frameshift mutations
A published solution is not available for this question yet.
Report a correction for Q21
Question 22 MCQ · 3.0 marks 6406532754632. (1), (A), (i); (2), (B), (ii); (3), (A), (ii); (4), (B), (i);
6406532754633. (1), (B), (i); (2), (B), (i); (3), (A), (ii); (4), (A), (ii);
6406532754634. (1), (A), (ii); (2), (A), (i); (3), (B), (i); (4), (A), (i);
6406532754635. (1), (B), (ii); (2), (B), (i); (3), (B), (i); (4), (A), (ii);
A published solution is not available for this question yet.
Report a correction for Q22
Question 23 MCQ · 3.0 marks 6406532754636. 6406532754637. 6406532754638. 6406532754639. A published solution is not available for this question yet.
Report a correction for Q23
Question 24 MCQ · 3.0 marks 6406532754640. 6406532754641. 6406532754642. 6406532754643. A published solution is not available for this question yet.
Report a correction for Q24
Question 25 MCQ · 3.0 marks 6406532754644. 6406532754645. 6406532754646. 6406532754647.
A published solution is not available for this question yet.
Report a correction for Q25
Question 26 MCQ · 3.0 marks 6406532754652. 6406532754653. 6406532754654. 6406532754655. A published solution is not available for this question yet.
Report a correction for Q26
Question 27 MCQ · 3.0 marks What is the average degree (regardless of the direction) of the 4-mer overlap graph constructed
from “GAATTCAGTTA”?
A published solution is not available for this question yet.
Report a correction for Q27
Question 28 MCQ · 3.0 marks What is the best local alignment score for the sequences "GTACTG" and "TAGTCTG" with the
scoring scheme: matches = +2, mismatches = -1 and a constant gap penalty of -10.
A published solution is not available for this question yet.
Report a correction for Q28
Question 29 MCQ · 3.0 marks Elucidate the final sequence that is obtained from the kmers: ’ATCG’, ’TACA’, ’TCGG’, ’CGGT’, ’CAAC’,
’GGTA’, GTAC’, ’ACAA’, ’AACT’, ’ACTC’.
6406532754668. ATCTGTACAACTC
6406532754669. ATCGGTACAACTC
6406532754670. ATCGGGACAACTC
6406532754671. ATCGGTATAACTC
A published solution is not available for this question yet.
Report a correction for Q29
Question 30 MCQ · 3.0 marks Consider the following statements:
**Assertion (A):** Eulerian Path algorithm is preferred over the Hamiltonian Path algorithm for the
genome assembly problem.
**Reason (R):** A Hamiltonian Path passes through all the nodes of a graph.
Now which of the following options is true:
6406532754672. Both A and R are true and R is the correct explanation for A
6406532754673. Both A and R are true and R is not the correct explanation for R
6406532754674. A is true but R is false
6406532754675. Both the statements are false
A published solution is not available for this question yet.
Report a correction for Q30
Question 31 MSQ · 3.0 marks What are the key features of convolutional layers in graph neural networks?
6406532754624. Equivariant representation
6406532754625. Sparse connections
6406532754626. Parameter sharing
6406532754627. Can be extended to data with high dimensions
A published solution is not available for this question yet.
Report a correction for Q31
Question 32 MSQ · 3.0 marks What are the limitations of shallow embeddings?
6406532754628. Shallow embedding methods share parameters between nodes in the encoder
6406532754629. Shallow embedding approaches do not leverage node features in the encoder
6406532754630. Shallow embedding methods can only generate embeddings for nodes that
were present during the training phase
6406532754631. Shallow embedding methods directly optimizes a unique embedding vector for
each node
A published solution is not available for this question yet.
Report a correction for Q32
Question 33 MSQ · 3.0 marks Which of the following are true for graph filters:
6406532754648. Spatial-based graph filters explicitly leverage the graph structure
6406532754649. Spectral-based graph filters utilize spectral graph theory to design the filtering
operation in the spectral domain
6406532754650. Cheby-Filter is a spatial-based graph filter
6406532754651. GAT-Filter is a spatial-based graph filter
A published solution is not available for this question yet.
Report a correction for Q33
Question 34 MSQ · 3.0 marks Which of the following can we use alignment for?
6406532754660. To identify mutations in a given sequence
6406532754661. To search in a database based on a query
6406532754662. To discover conserved regions in a gene
6406532754663. Generating overlap graphs from k-mer reads
A published solution is not available for this question yet.
Report a correction for Q34
Question 35 MCQ · 2.0 marks 6406532754676. i-a, ii-b, iii-c iv-d
6406532754677. i-d, ii-c, iii-a, iv-b
6406532754678. i-b, ii-c, iii-d, iv-a
6406532754679. i-c, ii-d, iii-b, iv-a
A published solution is not available for this question yet.
Report a correction for Q35
Question 36 MCQ · 2.0 marks 6406532754684. Both the assertion and reason are true and the reason is the correct
explanation for the assertion
6406532754685. Both the assertion and reason are true. But the reason is not correct regarding
the assertion.
6406532754686. Only the Assertion is true.
6406532754687. Only the Reason is true.
A published solution is not available for this question yet.
Report a correction for Q36
Question 37 MCQ · 2.0 marks 6406532754688. A - 2, B - 1, C - 4, D - 3
6406532754689. A - 4, B - 3, C - 1, D - 2
6406532754690. A - 4, B - 2, C - 1, D - 3
6406532754691. A - 3, B - 2, C - 4, D – 1
A published solution is not available for this question yet.
Report a correction for Q37
Question 38 MCQ · 2.0 marks What is the significance of the ddNTPs in Sanger sequencing?
6406532754704. It allows for rapid sequencing of long DNA fragments.
6406532754705. It enables the synthesis of complementary DNA strands.
6406532754706. It enables rapid sequencing of DNA sample.
6406532754707. It provides sequence-specific terminaon of DNA synthesis.
A published solution is not available for this question yet.
Report a correction for Q38
Question 39 MCQ · 2.0 marks Which out of the following sequences is typically found at the end of a transcribed gene?
6406532754708. Start codon
6406532754710. Promoter sequence
6406532754711. Enhancer sequence
A published solution is not available for this question yet.
Report a correction for Q39
Question 40 MCQ · 3.0 marks What is the sequence obtained from the gel picture given below.
6406532754680. 5’-ATATTACGGTAG-3’
6406532754681. 5’-ATAGTGTCGTAG-3’
6406532754682. 5’-ATAGTCTCGTAG-3’
6406532754683. 5’-ATATGCTAGTAG-3’
A published solution is not available for this question yet.
Report a correction for Q40
Question 41 MCQ · 1.0 marks Answer the given subquestions from the given image below
Identify the plot
6406532754692. Circos Plot
6406532754694. Manhatan Plot
A published solution is not available for this question yet.
Report a correction for Q41
Question 42 MCQ · 1.0 marks Answer the given subquestions from the given image below
What does the red horizontal line at y=6 represents?
6406532754696. Statistical cut off below which the values are significant.
6406532754697. Maximum threshold value of -Log10(P) value.
6406532754698. Statistical cut off above which the values are significant
6406532754699. None of these
A published solution is not available for this question yet.
Report a correction for Q42
Question 43 MCQ · 1.0 marks Answer the given subquestions from the given image below
Based on the plot which of the chromosomes have significant SNP(s).
6406532754700. Chromosome 1
6406532754701. Chromosome 10
6406532754702. Chromosome 19
6406532754703. None of these
**Sw Engg**
**Section Id :** 64065357823
**Section Number :** 2
**Section type :** Online
**Mandatory or Optional :** Mandatory
**Number of Questions :** 26
**Number of Questions to be attempted :** 26
**Section Marks :** 100
**Display Number Panel :** Yes
A published solution is not available for this question yet.
Report a correction for Q43
