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Question Bank- Bioinfo-II
1. Discuss the flow of information stored in the DNA to protein.
2. Discuss Homology identification in biological sequence alignment. Differentiate
between Orthologous and Paralogous genes.
3. Descibe the procedure of protein structure prediction through homology modeling.
4. Define Genome annotation. Explain its importance. Explain sequence-to-structure-tofunction paradigm.
5. Explain similarity based approach to Gene prediction.
6. Briefly discuss the various methods of protein structure prediction
7. Discuss the method of ORF finding in genome sequence.
8. What is microarray gene expression and discuss the clustering of microarray data.
9. What do you mean by inference problems in molecular biology? Explain with a
suitable example.
10. Enumerate few key inference problems in molecular biology.
11. Describe any one method for protein structure prediction.
12. What do you mean by protein function prediction? How is it done, explain with a
suitable example.
13. What is drug discovery? Explain various steps of drug discovery.
14. What is network identification, explain with suitable examples.
15. Briefly enumerate the various methods of protein structure prediction.
16. What do you understand by gene regulatory network? Explain with a suitable
example.
17. Discuss the current methods for genome sequencing and importance of genomic
sequence annotation.
1. Describe the advantage of clustering techniques in computational molecular biology.
2. Discuss the various application of regression analysis in bioinformatics.
3. Explain the concept of dimensionality reduction and its utility in solving the molecular
biology problems
4. Describe Regression and statistical inference methods applied in bioinformatics
analysis.
5. What is Baye’s rule? Explain Baye’s theorem applicable in biological system.
7. Explain applications of statistics in Bioinformatics.
8. Explain applications of probability and statistics in Bioinformatics.
9. Describe Regression and Significance testing methods applied in bioinformatics
analysis.
10. Explain the Baye’s rule application in biological sequence analysis.
11. Discuss the regression and significance testing, statistical inference methods applied
in bioinformatics analysis.
13. Define Computational induction technique for density evaluation.
14. Differentiate between clustering and discrimination process.
15. What do you mean by dimensionality reduction?
1. What is artificial neural network? Discuss the application of feed forward back
propagation method in protein structure prediction
2. Discuss the application SVM in subunit vaccine design.
3. Discuss a machine learning algorihm used for optimal pairwise sequence alignment.
4. Descriobe the application and limitations of machine learning approaches.
5. Explain application of GA in Bioinformatics.
6. Discuss the concept of neural networks and their applications in computational
molecular biology.
7. Briefly explain parametric tests, cross validation and empirical significance testing.
8. Enumerate various machine learning approaches used in computational biology.
9. What is GA? Explain with suitable example.
10. What is artificial neural network? Explain the application of back propagation method
with suitable example.
11. What do you mean by supervised learning and AND DISCUSS the training of back
propagation ANN for classification task
12. What is GA? How it is applied to solve biological problems.
13. Define the evaluation parameter sensitivity, specificity, correlation coefficient and
accuracy.
14. Describe the machine learning process with diagrammatic representation.
15. Discuss the neural network and SVM with example.
16. What do you mean by machine learning process and discuss the HMM model for
profile generation?
17. Discuss the application of SVM for classification task with example.
18. Explain the ROC curve for cross-validation and significance testing.
1. What is biological bibliography database? Give an example of such a database.
2. Briefly discuss Chou-Fasman algorithm for secondary structure prediction of proteins
3. What do you understand by sensitivity analysis of a bioinformatics software tool.
4. What are differential equation simulators, explain with suitable examples
5. Explain Discrete and Hybrid simulation and application in molecular biology.
6. Give the name two most common computational operations performed in continuous
simulation with suitable examples.
7. Discuss how large biological documents are managed.
8. Explain different data mining methods.
9. What is Data mining? Explain data mining applications in genomic sequences.
10. Describe the general simulation techniques applicable to biological problems
11. Explain continuous simulation in biological processes.
12. How management information is applied in Bioinformatics.
13. Describe the simulation processes used in Bioinformatics.
14. Describe the retrieval system for a biological database.
15. Discuss the RDBMS techniques for biological database management.
16. Discuss the general modeling and simulation process applicable to most problems in
Bioinformatics with flow chart.
17. Explain continuous simulation, discrete simulation and hybrid simulation.
18. Give the name of two most common computational operations performed in
continuous simulation and explain in briefly.
19. Define Data mining. Explain data mining operations in context of a larger knowledge
discovery process.
20. Describe the Monte Carlo process of simulation.
1. Discuss the procedure for microarray data analysis and various software tools used for
the purpose.
2. How Bioinformatics can help in novel drug design? What is QSAR analysis?
3. What is Pharmacogenomics? Mention their applications in drug discovery.
4. Explain any one method for protein –ligand docking in drug designing.
5. Discuss the recent trends in computational drug design.
6. Devise an algorithm to compute the number of distinct optimal alignments between a
pair of strings.
7. Suggest a computational strategy for Homology based 3-D protein structure modeling.
8. What do you mean by protein-ligand docking? Explain with suitable example.
9. Discuss the recent trends in computational vaccine designing.
10. Discuss any one computational method for 3-D structure modeling.
11. Describe the importance of literature databases in Bioinformatics.
12. Define RMSD and discuss the structural alignment process in protein-protein
interaction.
13. Derive an algorithm to compute the number of distinct optimal alignment between a
pair of strings.