GRN (P2)
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- Q1In a graph model of a Gene Regulatory Network (GRN), what do the nodes and edges typically represent?Nodes represent DNA sequences, and edges represent mutational relationships.Nodes represent cellular functions, and edges represent physical cell-cell interactions.Nodes represent proteins, and edges represent metabolic pathways.Nodes represent genes or gene products (such as proteins), and edges represent regulatory interactions.60s
- Q2Which type of network analysis is more informative?Retrospective Lineage TracingProspective Lineage TracingDynamical ModellingStatic Network Analysis60s
- Q3How can scientists build biological networks?Using databasesBy making predictionsThrough experimentsAll of the above60s
- Q4In GRN, what does a directed graph indicate?Edges do not have an exact direction.There is no interaction between nodes.Edges are oriented, indicating modulation.Only physical interactions are considered.60s
- Q5What are nodes in a biological network often representative of?Only transcription factorsOnly proteinsGenes, mRNAs, TFs, etc.Only genes60s
- Q6What is a key difference between static and dynamic network analysis in studying gene regulatory networks?Static network analysis identifies cell types, while dynamic does not.Static network analysis focuses on gene expression equilibrium, whereas dynamic does not.Only static network analysis can determine cluster-based gene expression similarity.Dynamic network analysis captures the temporal evolution of the transcriptome, unlike static analysis.60s
- Q7Static network analysis does not provide information on:Cluster-based gene expression similarityGene expression equilibriumCell type identificationTemporal evolution of the transcriptome60s
- Q8Dynamical modelling in GRN inference is based on:Gene expression measured at several time pointsGene expression measured at one time pointStatic state gene expression analysisOnly the final state of gene expression60s
- Q9Which type of experiment involves perturbing cells and observing changes over time?Static network analysisRetrospective lineage tracingDynamical modellingProspective lineage tracing60s
- Q10Single cell RNA-seq is increasingly used for:Lineage trajectories and determining cell fateOnly cell classificationOnly determining cell fateOnly trajectory analysis60s
- Q11Which mathematical representations are utilized in biological network analysis?Neural networks onlyLinear equations onlyDirected and undirected graphsPhysical maps only60s
- Q12
What is true about the edges (or links) in biological networks? (Choose all thatapply)
I. Represent physical interactions betweenmolecular components
II. Can indicate both activation andinhibition
III. Are always unidirectional
IV. Encode conditional dependencies betweengenes
I & II
III & IV
I, III & IV
All of the above
60s - Q13
Which approach is used for retrospective lineage tracing? (Choose all that apply)
I. Prospective lineage tracing
II. Static network analysis
III. Dynamical modelling
IV. Physical interaction mapping
All of the above
III only
I & IV
II &III
60s - Q14
Which of the following methods is used to obtain biological networks? (Choose all that apply)
I. A collection of databases
II. High-throughput experiments
III. Manual observations
IV. Large-scale bioinformatics predictions
III
I & II
IV
I, II & IV
60s - Q15
Which of the following are true about Gene Regulatory Networks (GRN)? (Choose all that apply)
I. Involve the regulation of one gene by another.
II. Include protein-to-gene feedback loops.
III. Solely based on physical interactionbetween genes.
IV. Can be simple or highly complexdepending on the number of genes involved.
I, II & IV
IV
III
I & II
60s