Search & Filtering
(a) Why must the inside of a spectrometer kept at a high vacuum?
(b) How are molecular ions formed? What information could be obtained from
mass/charge value of a molecular ion?
(c) Define Ion Trap, ICR, Quadrupole and Octapole.
(a) A researcher is scanning a cDNA microarray and obtains an image with the following characteristics: most of the spots are visible and many are very bright; the background appears to be light gray. The researcher proceeds to the image processing and quantification stages and finds that most spots appear to be characterized by a high average intensity. Discuss what might have happened? What steps would you undertake in order to test your hypothesis and correct the situation?
(b) What experiment can be used as an alternative to microarray analysis? What are its advantages over the former?
(c) What is the difference between concordant, discordant and unmapped reads?
What are some issues associated with adapting multiple sequence alignment programs to large genomic sequences?
(a) What is a sequence pattern? Explain the use of patterns for functional annotation.
(b) What are True positive, True negative, False positive, and False-negative in the context of pattern searches in protein sequences? How to obtain sequence patterns?
(a) What are low complexity regions and how are they handled in database searching and why?
(b) What is the importance of E-value in database searching?
(a) Distinguish between the programs BLASTP, BLASTN, BLASTX, TBLASTN,
TBLASTX of the BLAST package.
(b) Give a brief discussion of programs, PHI-BLAST, and PSI-BLAST. How is PSI- BLAST used in multiple sequence alignment?
(a)What is RMSD and what is it used for?
(b) Proteins are not rigid, but flexible. How could the RMSD definition be modified to cope with flexibility? Give the advantages and disadvantages of the basic RMSD definition and
your modification.
(a) Explain the energy landscape model for protein folding with appropriate illustrations.
(b) What is the principle of minimal frustration?
(a) Hidden Markov models (HMM) are used to identify genes in genome sequencing projects. Describe how you would build a hidden Markov model to identify genes in a genome sequence.
(b) Give one other application of hidden Markov models.
(a) Explain sensitivity and selectivity in terms of true and false positives.
(b) What is the advantage of a Needleman-Wunsch alignment compared to a seeded alignment?
(c) What does the expectation parameter mean in local alignment? What will happen if the expectation value is increased from its default value of 10 to a 100?
