Denoising large-scale biological data using network filters

Denoising large-scale biological data using network filters

Background: Large-scale biological data sets are often contaminated by noise, which can impede accurate inferences about underlying processes. Such measurement noise can arise from endogenous biological factors like cell cycle and life history variation, and from exogenous technical factors like sam...

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Bibliographic Details
Main Authors: Clauset, A. (Author), Kavran, A.J (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Accurate inference
algorithm
Algorithms
Biological factors
Biological signals
Correlation patterns
Denoising
diffusion
Diffusion
human
Humans
image processing
Image Processing, Computer-Assisted
Interaction networks
Machine learning
Measurement Noise
neoplasm
Neoplasms
Network structures
Networks
Proteomics
Sample preparation
signal noise ratio
Signal processing
Signal-To-Noise Ratio
Turing machines
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