Advanced Database Management System - Tutorials and Notes: EC9073 - Bioinformatics - April May 2014

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EC9073 - Bioinformatics - April May 2014

Anna University Questions - EC9073 Bioinformatics April May 2014, Computer Science and Engineering (CSE), Seventh semester, Regulation 2008




Exam
B.E/B.Tech. (Full Time) DEGREE END SEMESTER EXAMINATIONS
Academic Year
April May 2014
Subject Code

EC9073

Subject Name

Bioinformatics

Branch
Computer Science and Engineering
Semester
Seventh Semester
Regulation
2008

B.E / B.Tech. (Full Time) DEGREE END SEMESTER EXAMINATIONS, APRIL / MAY 2014
Computer Science and Engineering
Seventh Semester
EC9073 BIOINFORMATICS
(Regulation 2008)
Time : 3 Hours                      Answer A L L Questions                Max. Marks 100
PART-A (10 x 2 = 20 Marks)

1. What are the structural domain resources?
2. What is the need of bio informatics technologies?
3. Give short note on data quality.
4. How machine learning is used in bioinformatics?
5. List out the major steps used in PHMM generation.
6. How Bayesian networks used in modeling for bioinformatics?
7. What are the important problems in DNA and protein sequence analysis?
8. Give the unique function of promoters.
9. What are the methods used to extract the significant modes of variation from the large array of time series expression data?
10. What is gene expression profiling?

Part-B (5* 16 = 80 Marks)

11. (i) How can the secondary resources and associated algorithms be grouped? Discuss in detail. (12)
(ii) Explain in detail about the drug discovery (4)

12. a (i) With neat sketch, explain data ware housing architecture in detail (8)
(ii) Explain in detail about DNA data analysis (8)
(OR)
b (i) Explain in detail about Protein data analysis (8)
(ii) With necessary diagrams detail different learning algorithms used in neural networks. (8)

13. a. Explain briefly about Hidden Markov model for biological data analysis (16)
(OR)
b. Detail comparative and molecular modeling for biological data analysis (16)

14. a.(i) Explain two dimensional portrait representation of DNA sequences (8)
(ii) Discuss Chaos Game Representation of biological sequences (8)
(OR)
b.(i) Explain different DNA walk models in detail (8)
(ii) Discuss different approaches of motif detection with a sample pattern (8)

15. a Explain briefly about Image analysis for data extraction (16)
(OR)
b Elaborate data analysis for pattern discovery. (16)

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