نخستین همایش ریاضیات زیستی , 2019-03-12

Title : ( Persistent homology for prediction of protein folding )

Authors: Bibi Hanieh Mirebrahimi Paziquee , Ameneh Babaee , Azam babaee ,

Citation: BibTeX | EndNote

Abstract

Topological data analysis in an approach to use topological techniques for analysis of datasets. Persistent homology is one of the main tools of topological data analysis used for reducing the dimension and complexity of the data sets, and also to distinguish topological features and delete noises. Site directed mutagenesis is widely used to understand the structure and function of biomolecules. Computational prediction of protein mutation impacts offers a fast, economical and potentially accurate alternative to laboratory mutagenesis. In this talk, topology based mutation predictor -T-MP- is introduced to dramatically reduce the geometric complexity and number of degrees of freedom of proteins, while element specific persistent homology is proposed to retain essential biological information. The present approach is found to outperform other existing methods in globular protein mutation impact predictions.

Keywords

, persistent homology, protein folding, topological data analysis
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@inproceedings{paperid:1073777,
author = {Mirebrahimi Paziquee, Bibi Hanieh and Babaee, Ameneh and اعظم بابایی},
title = {Persistent homology for prediction of protein folding},
booktitle = {نخستین همایش ریاضیات زیستی},
year = {2019},
location = {نیشابور, IRAN},
keywords = {persistent homology; protein folding; topological data analysis},
}

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%0 Conference Proceedings
%T Persistent homology for prediction of protein folding
%A Mirebrahimi Paziquee, Bibi Hanieh
%A Babaee, Ameneh
%A اعظم بابایی
%J نخستین همایش ریاضیات زیستی
%D 2019

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