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+++ b/paper.tex
@@ -70,21 +70,29 @@
 
 
 \section{Introduction}
-
+Possible points to mention here:
+\begin{itemize}
+	\item Explain shortly gene regulatory networks (GRN)
+	\item Explain why boolean networks are used to model GRN
+	\item Maybe mention history of boolean networks
+	\item Set the focus to the update scheme as it seems to be rarely covered in the field of GRNs
+	\item Possible open question about which update scheme might be best to model GRNs. Answer to this must follow in the conclusion
+\end{itemize}
 
 
 \section{Boolean networks}
-Explain Boolean network and what an update scheme is using the synchronous/parallel scheme.
+Explain Boolean network and what an update scheme is using the synchronous/parallel scheme. Also use figure, e.g. \cref{fig:boolean_example} to further visualize and create a better understanding of boolean networks. Also explain what chaotic behavior is due its relevance for the update schemes.
 
 \subsection{Notation}
-Define clear notation used throughout the paper
+Define clear notation used throughout the paper. Position of this subsection could change to be part of the Introduction instead.
 
 
 
 \section{Update Schemes}
-Explain different update schemes including characteristics for behavior especially chaotic behavior.
+Explain different update schemes including characteristics for behavior especially chaotic behavior. These will mostly focus on boolean networks only. Maybe mention of use-cases for each update scheme.
+
 \subsection{Synchronous scheme}
-all nodes update at the same time
+The Synchronous (also known as Parallel) update scheme assumes that every node is updated at once.
 \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}
@@ -96,26 +104,30 @@ same as asynchronous deterministic with the slight change that within the sequen
 
 
 \section{Relevance for Gene Regulatory Networks}
+\label{sec:relevance_grn}
 Tie the update schemes and their different outcomes or behavior to GRN.
 
 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}
+Not yet included: robustness! might be covered for each update scheme individually.
+
 References: \cite{schwab2020concepts}\cite{aracena2009robustness}\cite{bornholdt2008boolean}\cite{goles2010block}\cite{helikar2011boolean}
 
 
 
-\begin{figure*}  % The starred version uses both columns; unstarred only one column
+\begin{figure}  % The starred version uses both columns; unstarred only one column
 	\centering
-	% \includegraphics[width=5in]{edge_vs_hyperedge.png}
+	\includegraphics[width=3in]{4bit BN.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*}
+	\caption{Boolean example (image will be changed!).
+		% 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 $x(t) \rightarrow x(t+1)$ (currently missing)
+	}
+\label{fig:boolean_example}
+\end{figure}
 
 \begin{figure*}  % The starred version uses both columns; unstarred only one column
 	\centering