Which of the following is true about Expectation Maximization (EM) method?(a) The log odds scores of the PSSM are modified at the end of the process(b) The procedure stops prematurely if the scores reach convergence(c) The final result is not sensitive to the initial alignment(d) Local optimum is an advantage of EM methodThis question was posed to me in class test.My question is taken from Motif Discovery in Unaligned Sequences in chapter Sequence Alignment of Bioinformatics

Which of the following is true about Expectation Maximization (EM) met

1.	Which of the following is true about Expectation Maximization (EM) method?(a) The log odds scores of the PSSM are modified at the end of the process(b) The procedure stops prematurely if the scores reach convergence(c) The final result is not sensitive to the initial alignment(d) Local optimum is an advantage of EM methodThis question was posed to me in class test.My question is taken from Motif Discovery in Unaligned Sequences in chapter Sequence Alignment of Bioinformatics
Answer» Right answer is (B) The procedure stops prematurely if the scores reach convergence To explain: The FINAL result is SENSITIVE to the initial alignment. The LOCAL optimum is actually a drawback of EM method. It is same as the fact that the procedure stops prematurely if the scores reach convergence.

Discussion

No Comment Found

Related InterviewSolutions

Unlike the commonly used methods for aligning a pair of sequences, the Bayesian method _______ using a particular scoring matrix or designated gap penalties.(a) does not depend on(b) depends on(c) is based on(d) involvesI had been asked this question in an online quiz.This interesting question is from Bayesian Statistics in portion Sequence Alignment of Bioinformatics
Who suggested that the global alignment scores between unrelated protein sequences followed the extreme value distribution, similar to local alignment scores? And when?(a) Abagyan and Batalov, in 1981(b) Chvátal and Lipman, in 1984(c) Abagyan and Batalov, in 1997(d) Chvátal and Sankoff, in 1995This question was posed to me during an interview.I'd like to ask this question from Assessing the Significance of Sequence Alignments topic in portion Sequence Alignment of Bioinformatics
The higher is the score in the alignment _________(a) the more significant is the alignment(b) or the less it resembles alignments in related proteins(c) the less significant is the alignment(d) the less it aligns with the related protein sequenceThe question was posed to me during an online interview.The question is from Dynamic Programming Algorithm for Sequence Alignment topic in division Sequence Alignment of Bioinformatics
Isolated dots that are not on the diagonal represent exact matches.(a) True(b) FalseThis question was addressed to me in an online interview.This interesting question is from Dot Matrix Sequence Comparison in division Sequence Alignment of Bioinformatics
Which of the following is false in case of the database SMART and its algorithm?(a) Contains HMM profiles constructed from manually refined protein domain alignments(b) Alignments in the database are built based on tertiary structures whenever available or based on PSI-BLAST profiles(c) Alignments are further checked but not refined by human annotators before HMM profile construction(d) SMART stands for Simple Modular Architecture Research ToolI have been asked this question in semester exam.This intriguing question originated from Motif and Domain Databases Using Statistical Models in section Sequence Alignment of Bioinformatics
Which of the following is not an advantage of Needleman-Wunsch algorithm?(a) New algorithmic improvements as well as increasing computer capacity make it possible to align a query sequence against a large DB in a few minutes(b) Similar sequence region is of same order and orientation(c) This does not help in determining evolutionary relationship(d) If you have 2 genes that are already understood as closely related, then this type of algorithm can be used to understand them in further detailsI had been asked this question in class test.This is a very interesting question from Global Sequence Alignment in chapter Sequence Alignment of Bioinformatics
_______ analyzed the distribution of scores among 100 vertebrate nucleic acid sequences and compared these scores with randomized sequences prepared in different ways.(a) Lipman, in 1984(b) Batalov, in 1964(c) Waterman, in 1987(d) Lipman, in 1967This question was addressed to me in my homework.The question is from Assessing the Significance of Sequence Alignments topic in division Sequence Alignment of Bioinformatics
Which of the following doesn’t describe PAM matrices?(a) This family of matrices lists the likelihood of change from one amino acid to another in homologous protein sequences during evolution(b) There is presently no other type of scoring matrix that is based on such sound evolutionary principles as are these matrices(c) Even though they were originally based on a relatively small data set, the PAM matrices remain a useful tool for sequence alignment(d) It stands for Percent Altered MutationI had been asked this question during an interview for a job.My question is taken from Use of Scoring Matrices and Gap Penalties in Sequence Alignments topic in portion Sequence Alignment of Bioinformatics
In scoring matrices, for convenience, odds scores are converted to log odds scores.(a) True(b) FalseI had been asked this question during a job interview.This key question is from Use of Scoring Matrices and Gap Penalties in Sequence Alignments in portion Sequence Alignment of Bioinformatics
Which of the following does not describe k-tuple methods?(a) k-tuple methods are best known for their implementation in the database search tools FASTA and the BLAST family(b) They are also known as words methods(c) They are basically heuristic methods to find local alignment(d) They are useful in small scale databasesThe question was asked by my school principal while I was bunking the class.I'd like to ask this question from Local Sequence Alignment in portion Sequence Alignment of Bioinformatics

Discussion

No Comment Found

Related InterviewSolutions

Reply to Comment