Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis.

ABSTRACT:

Background

Biological processes are based on complex networks of cells and molecules. Single cell multi-omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell.

Methods

Since single cell technologies provide many sample measurements, they are the ideal environment for the application of Deep Learning and Machine Learning approaches. An autoencoder is composed of an encoder and a decoder sub-model. An autoencoder is a very powerful tool in data compression and noise removal. However, the decoder model remains a black box from which is impossible to depict the contribution of the single input elements. We have recently developed a new class of autoencoders, called Sparsely Connected Autoencoders (SCA), which

SUBMITTER: Alessandri L 

PROVIDER: S-EPMC8657975 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature