Persistent homology for protein folding analysis
Author:
, , , , ,Year
: 2019
Abstract: Persistent homology is a concept in topological data analysis used to reduce the dimensionality and
complexity of the data sets, and also to determine topological features and delete noises. In this talk,
unfolding process is simulated with the constant velocity pulling algorithm of SMD. Then, we apply
the persistent homology to reveal the topological features of intermediate configurations. Furthermore,
we construct a quantitative model based on the accumulation bar length A1 to predict the energy and
stability of protein configurations, which establishes a solid topology-function relationship of proteins with
the constant velocity pulling algorithm of SMD.
complexity of the data sets, and also to determine topological features and delete noises. In this talk,
unfolding process is simulated with the constant velocity pulling algorithm of SMD. Then, we apply
the persistent homology to reveal the topological features of intermediate configurations. Furthermore,
we construct a quantitative model based on the accumulation bar length A1 to predict the energy and
stability of protein configurations, which establishes a solid topology-function relationship of proteins with
the constant velocity pulling algorithm of SMD.
Keyword(s): persistent homology,protein folding,topological data analysis
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Persistent homology for protein folding analysis
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| contributor author | بی بی هانیه میر ابراهیمی پازیکوئی | en |
| contributor author | امنه بابایی | en |
| contributor author | اعظم بابایی | en |
| contributor author | Bibi Hanieh Mirebrahimi Paziquee | fa |
| contributor author | Ameneh Babaee | fa |
| contributor author | Azam Babaee | fa |
| date accessioned | 2020-06-06T14:30:33Z | |
| date available | 2020-06-06T14:30:33Z | |
| date copyright | 3/12/2019 | |
| date issued | 2019 | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3399731?locale-attribute=en | |
| description abstract | Persistent homology is a concept in topological data analysis used to reduce the dimensionality and complexity of the data sets, and also to determine topological features and delete noises. In this talk, unfolding process is simulated with the constant velocity pulling algorithm of SMD. Then, we apply the persistent homology to reveal the topological features of intermediate configurations. Furthermore, we construct a quantitative model based on the accumulation bar length A1 to predict the energy and stability of protein configurations, which establishes a solid topology-function relationship of proteins with the constant velocity pulling algorithm of SMD. | en |
| language | English | |
| title | Persistent homology for protein folding analysis | en |
| type | Conference Paper | |
| contenttype | External Fulltext | |
| subject keywords | persistent homology | en |
| subject keywords | protein folding | en |
| subject keywords | topological data analysis | en |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1073776.html | |
| identifier articleid | 1073776 |