Tag: PCA


  • tICA Metadynamics

    Time-lagged independent component analysis is a dimensionality reduction technique which transforms a high dimensional dataset to lower dimensional co-ordinates. It’s philosophy is kind of similar to PCA (principal component analysis).  For more details check here. It is a very recently developed technique which has a lot of promise. tICA can separate slow degrees of freedom […]

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  • Possible new idea with tSNE

    Dimensionality reduction is in the hurt of molecular dynamics simulations keeping in mind its importance in reducing the high-dimension data produced during molecular dynamics simulations. It also found application in building Markov State Models and also used as CVs to drive enhanced sampling simulations. Several dimensionality reduction techniques have been used over the years  such […]

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  • Analysis of MD trajectory using tSNE

    Before starting anything with tSNE let’s read what is tSNE and how it has been compared with PCA. You can read it here. Several implementations of t-SNE are available here. A great introductory video on tSNE can be found here. The dataset used in this explanation can be accessed here (named combine_times_ca.dcd and corresponding GRO file […]

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