Aug 7, 2022 · In this paper, we directly compare autoencoders performance as a dimensionality reduction technique (via the latent space) to other established ...
Aug 10, 2022 · ABSTRACT. Large-scale data often suffer from the curse of dimensionality and the constraints associated with it; therefore, dimensionality ...
Here, dimensionality reduction algorithm is introduced to predict the quaternary structure of proteins. Our jackknife test results indicate that it is very ...
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Dimensionality reduction transforms a high-dimensional dataset into a representation with fewer dimensions, while retaining the key relationships among samples ...
Mar 13, 2021 · Analysis of the high-dimensional mass spectrometric (MS) data usually employs dimensionality reduction (DR) algorithms as the preliminary step ...
Apr 1, 2023 · This calls for the evaluation and development of computational methods specific for CyTOF data. Dimension reduction (DR) is one of the critical ...
Aug 25, 2016 · We compared classification accuracy and running time of different combination methods on three microarray datasets and a simulation dataset.
Nov 8, 2023 · Dimensionality reduction techniques are essential in analyzing large 'omics' datasets in biochemistry and molecular biology.
This work investigates how both discrete and continuous structures in biological data can be captured using the recently proposed dimensionality reduction ...
PDF | This research focuses on big data visualization that is based on dimensionality reduction methods. We propose a multi-level method for data.