HMM'S INTERPOLATION OF PROTIENS FOR PROFILE ANALYSIS

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Authors: Neeshu Sharma
Cited by: 0

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.

Fields of Study & Subjects

Genomics and Phylogenetic Studies Machine Learning in Bioinformatics Protein Structure and Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
18 February 2026
Language
EN