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Ontology on April 27, 2023

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Representing and extracting knowledge from single cell data. (arXiv:2304.13084v1 [q-bio.GN])

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Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of advanced statistics and machine learning. This review attempts to explain the deeper theoretical concepts that underpin current state-of-the-art analysis methods. Single-cell analysis is covered from cell, through instruments, to current and upcoming models. A minimum of mathematics and statistics has been used, but the reader is assumed to either have basic knowledge of single-cell analysis workflows, or have a solid knowledge of statistics. The aim of this review is to spread concepts which are not yet in common use, especially from topology and generative ...

arXiv Apr 27, 2023

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