Tom/Gene-Regulatory-Networks-Seminar
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small update and restructure before deadline. not yet uploaded!

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Tom Zuidberg
2026-04-26 23:03:16 +02:00
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paper.tex
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@@ -15,7 +15,7 @@
%pdfauthor=,
colorlinks=true, linkcolor=purple, urlcolor=blue, citecolor=cyan,
anchorcolor=black % make links/references 'clickable' without ugly frames
]{hyperref}
]{hyperref}
\usepackage{cleveref} % smart references to figures, equations etc.
% some packages which may be useful when drafting, but should be removed before submission
@@ -69,49 +69,52 @@
\end{abstract}
\section{Introduction}00
\subsection{Notation}
\section{Introduction}
\section{Boolean networks}
Explain Boolean network and what an update scheme is using the synchronous/parallel scheme.
\subsection{Notation}
Define clear notation used throughout the paper
\section{Update Schemes}
Explain different update schemes:
\begin{itemize}
\item Synchronous scheme - all nodes update at the same time
\item Sequential - close to synchronous. the nodes update in a specific order and take into account the updated input node if that node had been updated before/is positioned earlier in the sequence
\item block sequential - mix of synchronous and sequential. predefined blocks update sequentiall, inside a block the update follows the synchronous scheme
\item asynchronous deterministic - one node is updated per tick following a specific sequence
\item asynchronous generalized - same as asynchronous deterministic with the slight change that within the sequence nodes may appear multiple times.
\end{itemize}
Explain different update schemes including characteristics for behavior especially chaotic behavior.
\subsection{Synchronous scheme}
all nodes update at the same time
\subsection{Sequential scheme}
close to synchronous. the nodes update in a specific order and take into account the updated input node if that node had been updated before/is positioned earlier in the sequence
\subsection{Block-sequential scheme}
mix of synchronous and sequential. predefined blocks update sequential, inside a block the update follows the synchronous scheme
\subsection{Asynchronous deterministic}
one node is updated per tick following a specific sequence
\subsection{Asynchronous generalized}
same as asynchronous deterministic with the slight change that within the sequence nodes may appear multiple times.
\section{Relevance for Gene Regulatory Networks}
Tie the update schemes and their different outcomes or behavior to GRN.
\section{Conclusion}
Emphasizing the drawbacks of asynchronous models when applied to GRN e.g. it takes way to long to update a GRN using asynchronous deterministic for it to have an effect; assuming that one update takes a few minutes, when the whole process can take days to complete.\cite{schwab2020concepts}
\section{Conclusion}
References: \cite{schwab2020concepts}\cite{aracena2009robustness}\cite{bornholdt2008boolean}\cite{goles2010block}\cite{helikar2011boolean}
\begin{figure*} % The starred version uses both columns; unstarred only one column
\centering
% \includegraphics[width=5in]{edge_vs_hyperedge.png}
% \includegraphics[width=5in]{edge_vs_hyperedge.png}
% TIP: Ensure the original image file has approximately the right dimensions
% (if using matplotlib, specify correct figure size) so that the image is not rescaled too brutally.
\caption{Boolean example.
% NB: The '~' inserts a non-breaking space, ensuring 'Ref.' is never separated from its number
Simple boolean network example; a graph of the network and most likely a table as well for the updated states $x(t) \rightarrow x(t+1)$
}
\end{figure*}
\begin{figure*} % The starred version uses both columns; unstarred only one column
@@ -120,18 +123,18 @@ Tie the update schemes and their different outcomes or behavior to GRN.
\caption{
graph of all possible states for a boolean network using a synchronous update scheme
}
\end{figure*}
\begin{figure*} % The starred version uses both columns; unstarred only one column
\centering
% \includegraphics[width=5in]{edge_vs_hyperedge.png}
% \includegraphics[width=5in]{edge_vs_hyperedge.png}
% TIP: Ensure the original image file has approximately the right dimensions
% (if using matplotlib, specify correct figure size) so that the image is not rescaled too brutally.
\caption{
example graph of boolean network showcasing grouping of specific nodes.
}
\end{figure*}