May 28, 2009 · In this paper, we propose a methodology for making sense of large, multiple time-series data sets arising in expression analysis.
In this paper, we propose a methodology for making sense of large, multiple time-series data sets arising in expression analysis. Specifically, we present a ...
Oct 22, 2024 · In this paper, we propose a methodology for making sense of large, multiple time-series data sets arising in expression analysis.
A mathematical program to refine gene regulatory networks · G. Lulli, Martin Romauch · Published in Discrete Applied Mathematics 1 May 2009 · Biology, Computer ...
A mathematical program to refine gene regulatory networks. https://doi.org/10.1016/j.dam.2008.06.044 · Full text. Journal: Discrete Applied Mathematics, 2009 ...
A mathematical program to refine gene regulatory networks. Guglielmo Lulli, Martin Romauch. University of Milano Bicocca; Department of Business Administration ...
Dec 19, 2023 · This feature will introduce you to methods and talk you through how to model gene regulatory networks (GRNs).
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A mathematical program to refine gene regulatory networks ...
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In this paper, we propose a methodology for making sense of large, multiple time-series data sets arising in expression analysis. Specifically, we present a ...
Inferring gene regulatory networks from single-cell multiome data ...
www.nature.com › ... › articles
Apr 12, 2024 · Here we present LINGER (Lifelong neural network for gene regulation), a machine-learning method to infer GRNs from single-cell paired gene expression and ...
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This paper presents a mathematical framework for describing and analysing gene regulatory networks by autonomous differential equations.
Missing: program refine