HMM has found its application in almost every field. Applying Hmm to biological sequences has its own
advantages. HMM’s being more systematic and specific, yield a result better than consensus techniques.
Profile HMMs use position specific scoring for the matching & substitution of a residue and for the
opening or extension of a gap. HMMs apply a statistical method to estimate the true frequency of a residue
at a given position in the alignment from its observed frequency while standard profiles use the observed
frequency itself to assign the score for that residue. This means that a profile HMM derived from only 10 to
20 aligned sequences can be of equivalent quality to a standard profile created from 40 to 50 aligned
sequences.
%0 Journal Article
%1 noauthororeditor
%A Sharma, Er. Neeshu
%A Kumar, Er. Dinesh
%A Kaur, Er. Reet Kamal
%D 2011
%J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)
%K Analysis HMM Hmm Profile Sequence alignment
%N 3
%P 01-10
%R 10.5121/ijcseit.2011.1301
%T HMM’S INTERPOLATION OF PROTIENS FOR
PROFILE ANALYSIS
%U http://airccse.org/journal/ijcseit/papers/0811ijcseit01.pdf
%V 1
%X HMM has found its application in almost every field. Applying Hmm to biological sequences has its own
advantages. HMM’s being more systematic and specific, yield a result better than consensus techniques.
Profile HMMs use position specific scoring for the matching & substitution of a residue and for the
opening or extension of a gap. HMMs apply a statistical method to estimate the true frequency of a residue
at a given position in the alignment from its observed frequency while standard profiles use the observed
frequency itself to assign the score for that residue. This means that a profile HMM derived from only 10 to
20 aligned sequences can be of equivalent quality to a standard profile created from 40 to 50 aligned
sequences.
@article{noauthororeditor,
abstract = {HMM has found its application in almost every field. Applying Hmm to biological sequences has its own
advantages. HMM’s being more systematic and specific, yield a result better than consensus techniques.
Profile HMMs use position specific scoring for the matching & substitution of a residue and for the
opening or extension of a gap. HMMs apply a statistical method to estimate the true frequency of a residue
at a given position in the alignment from its observed frequency while standard profiles use the observed
frequency itself to assign the score for that residue. This means that a profile HMM derived from only 10 to
20 aligned sequences can be of equivalent quality to a standard profile created from 40 to 50 aligned
sequences. },
added-at = {2018-10-30T12:29:24.000+0100},
author = {Sharma, Er. Neeshu and Kumar, Er. Dinesh and Kaur, Er. Reet Kamal},
biburl = {https://www.bibsonomy.org/bibtex/290467dd5f519a26acc141cdf55cd8d47/ijcseit},
doi = {10.5121/ijcseit.2011.1301},
interhash = {234c25e59d768c472ad292d076ee6aeb},
intrahash = {90467dd5f519a26acc141cdf55cd8d47},
issn = {2231-3117 [Online] ; 2231-3605 [Print]},
journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) },
keywords = {Analysis HMM Hmm Profile Sequence alignment},
language = {English},
month = aug,
number = 3,
pages = {01-10},
timestamp = {2018-10-30T12:29:24.000+0100},
title = {HMM’S INTERPOLATION OF PROTIENS FOR
PROFILE ANALYSIS},
url = {http://airccse.org/journal/ijcseit/papers/0811ijcseit01.pdf},
volume = 1,
year = 2011
}