Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.$

Because a protein-encoding gene is composed of nucleotides in triplets

1.	Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.$
A.	True
B.	False
Answer» B. False

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Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.
The use of Markov models in gene finding exploits the fact that oligonucleotide distributions in the coding regions are different from those for the noncoding regions.
Which of the following is a wrong statement regarding Gene Prediction Using Markov Models and Hidden Markov Models?
The conventional determination of open reading methods identify only typical genes and tend to miss atypical genes in which the rule of codon bias is not strictly followed.
WHICH_OF_THE_FOLLOWING_IS_A_WRONG_STATEMENT_REGARDING_GENE_PREDICTION_USING_MARKOV_MODELS_AND_HIDDEN_MARKOV_MODELS??$
Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.$
The use of Markov models in gene finding exploits the fact that oligonucleotide distributions in the coding regions are different from those for the noncoding regions.$
The conventional determination of open reading methods identify only typical genes and tend to miss atypical genes in which the rule of codon bias is not strictly followed?
Which of the following is a wrong statement regarding TESTCODE method?
The putative ORF can be translated into a protein sequence, which is then used to search against a protein database.

Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.$

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