Time-lagged t-distributed stochastic neighbor embedding (t-SNE) of molecular simulation trajectories

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22330%2F20%3A43920852" target="_blank" >RIV/60461373:22330/20:43920852 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60461373:22340/20:43920852

Výsledek na webu

<a href="https://www.frontiersin.org/articles/10.3389/fmolb.2020.00132/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fmolb.2020.00132/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fmolb.2020.00132" target="_blank" >10.3389/fmolb.2020.00132</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Time-lagged t-distributed stochastic neighbor embedding (t-SNE) of molecular simulation trajectories

Popis výsledku v původním jazyce

Molecular simulation trajectories represent high-dimensional data. Such data can be visualized by methods of dimensionality reduction. Non-linear dimensionality reduction methods are likely to be more efficient than linear ones due to the fact that motions of atoms are non-linear. Here we test a popular non-linear t-distributed Stochastic Neighbor Embedding (t-SNE) method on analysis of trajectories of 200 ns alanine dipeptide dynamics and 208 μs Trp-cage folding and unfolding. Furthermore, we introduce a time-lagged variant of t-SNE in order to focus on rarely occurring transitions in the molecular system. This time-lagged t-SNE efficiently separates states according to distance in time. Using this method it is possible to visualize key states of studied systems (e.g., unfolded and folded protein) as well as possible kinetic traps using a two-dimensional plot. Time-lagged t-SNE is a visualization method and other applications, such as clustering and free energy modeling, must be done with caution.

Název v anglickém jazyce

Time-lagged t-distributed stochastic neighbor embedding (t-SNE) of molecular simulation trajectories

Popis výsledku anglicky

Molecular simulation trajectories represent high-dimensional data. Such data can be visualized by methods of dimensionality reduction. Non-linear dimensionality reduction methods are likely to be more efficient than linear ones due to the fact that motions of atoms are non-linear. Here we test a popular non-linear t-distributed Stochastic Neighbor Embedding (t-SNE) method on analysis of trajectories of 200 ns alanine dipeptide dynamics and 208 μs Trp-cage folding and unfolding. Furthermore, we introduce a time-lagged variant of t-SNE in order to focus on rarely occurring transitions in the molecular system. This time-lagged t-SNE efficiently separates states according to distance in time. Using this method it is possible to visualize key states of studied systems (e.g., unfolded and folded protein) as well as possible kinetic traps using a two-dimensional plot. Time-lagged t-SNE is a visualization method and other applications, such as clustering and free energy modeling, must be done with caution.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Frontiers in Molecular Biosciences

ISSN

2296-889X

e-ISSN

—

Svazek periodika

7

Číslo periodika v rámci svazku

June

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

8

Strana od-do

"132-1"-"132-8"

Kód UT WoS článku

000555944200001

EID výsledku v databázi Scopus

2-s2.0-85087831668