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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