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Update table layout
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cthoyt committed Jun 25, 2019
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\usepackage{url}
\usepackage{graphicx} % used to add figures
\usepackage{multirow}
\usepackage{makecell}

%\usepackage[applemac]{inputenc} %applemac support if unicode package fails
%\usepackage[latin1]{inputenc} %UNIX support if unicode package fails
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53 changes: 33 additions & 20 deletions implementation.tex
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Expand Up @@ -29,33 +29,47 @@ \subsubsection*{Definition of data}
For those that are versioned, providers commonly generate symlinks to the most recent version (e.g., InterPro; \url{ftp://ftp.ebi.ac.uk/pub/databases/interpro}).
These characteristics help minimize licensing issues while enabling the resulting packages to update their content without changing code.
Then, the developer implements custom code that makes the appropriate interpretations to convert the source data to BEL.
Below, three types of data that can be readily integrated in BEL are described along with accompanying Table~\ref{tab:statements}.
Below, three types of data that can be readily integrated in BEL are described along with accompanying Table~\ref{tab:statements1},~\ref{tab:statements2},and~\ref{tab:statements3}.

\begin{table}[h!]
\caption{Example BEL statements generated by several different types of data sources}
\label{tab:statements}
\begin{tabular}{llll}
\caption{Taxonomies, Hierarchies, and Ontologies}
\label{tab:statements1}
\begin{tabular}{lll}
\hline
Data Source Type
& Data Source & Example BEL Statement & Description \\
Data Source & Example BEL Statement & Description \\
\hline
\multirow{3}{*}{Taxonomies, Hierarchies, and Ontologies}
& MeSH & path(X) isA path(Y) & Pathology X is a subtype of pathology Y. \\
& Complex Portal & p(X) partOf complex(Y) & Protein X is a member of complex Y. \\
& GO & bp(X) partOf bp(Y) & Biological process X is a sub-process of Y. \\
MeSH & path(X) isA path(Y) & Pathology X is a subtype of pathology Y. \\
Complex Portal & p(X) partOf complex(Y) & Protein X is a member of complex Y. \\
GO & bp(X) partOf bp(Y) & Biological process X is a sub-process of Y. \\
\end{tabular}
\end{table}

\begin{table}[h!]
\caption{Tabular and Relational Data}
\label{tab:statements2}
\begin{tabular}{lll}
\hline
Data Source & Example BEL Statement & Description \\
\hline
PubChem, ChEMBL & a(X) directlyDecreases act(p(Y), ma(kin)) & Compound X inhibits kinase Y. \\
ADEPTUS & path(X) positiveCorrelation r(Y) & Gene Y is up-regulated in patients with pathology X. \\
ADEPTUS & path(X) negativeCorrelation r(Y) & Gene Y is down-regulated in patients with pathology X. \\
ADEPTUS & path(X) causeNoChange r(Y) & Gene Y is not regulated in patients with pathology X. \\
\end{tabular}
\end{table}

\begin{table}[h!]
\caption{Graphs}
\label{tab:statements3}
\begin{tabular}{lll}
\hline
\multirow{2}{*}{Tabular and Relational Data}
& PubChem, ChEMBL & a(X) directlyDecreases act(p(Y), ma(kin)) & Compound X inhibits kinase Y. \\
& ADEPTUS & path(X) positiveCorrelation r(Y)\newline
path(X) negativeCorrelation r(Y)\newline
path(X) causeNoChange r(Y)
& Gene Y has been observed to either be up-regulated, down-regulated, or unregulated in patients with pathology X. \\
Data Source & Example BEL Statement & Description \\
\hline
Graphs
& Menche \textit{et al.} & path(X) association path(Y) & Pathology X is statistically similar to pathology Y on the basis of gene overlap as defined by Menche \textit{et al.}~\cite{Menche2015}. \\
Menche \textit{et al.} & path(X) association path(Y) & Pathology X is statistically similar to pathology Y\\
\end{tabular}
\end{table}


\paragraph*{Taxonomies, hierarchies, and ontologies}

The Medical Subject Headings~\cite{ROGERS1963} multi-hierarchy can be converted to BEL by generating an isA relationship between each MeSH descriptor and all of its corresponding parents in the associated MeSH tree.
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Enzyme inhibitors from ChEMBL and PubChem can be encoded like a(X) directlyDecreases act(p(Y), ma(kin)), and disease-specific differential gene expression can be encoded like path(X) positiveCorrelation r(Y) or path(X) negativeCorrelation r(Y), or path(X) causeNoChange r(Y) depending on whether the gene's expression is up-regulated, down-regulated, or not regulated, respectively.
Further, BEL relationships can be extended include metadata (i.e., annotations) describing their quantitative aspects.
For example, $IC_{50}$, $EC_{50}$, or other kinetic assay measurements as well as provenance and biological contextual information (e.g., original publication, cell line, assay type) can be included with the enzyme inhibition relationships from ChEMBL\@.
Similarly, the $log_2$$ fold change and $p$-values can be included with relationships about differential gene expression.
Similarly, the $log_2$ fold change and $p$-values can be included with relationships about differential gene expression.

\paragraph*{Graphs}
Wet-laboratory experimentation can be used to generate networks of directly observed phenomena (e.g., protein-protein interaction networks) and indirectly observed phenomena (e.g., gene co-expression networks).
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Further, Bio2BEL packages can be generated by any group, and registered with the Bio2BEL framework using Python entry points (\url{https://packaging.python.org/specifications/entry-points}) that can be defined in the installation configuration.
While the Cookiecutter template allows new developers to quickly generate a package with the correct format, a full tutorial for implementing a uniform Bio2BEL package can be found at \url{https://bio2bel.readthedocs.io/en/latest/tutorial.html}.

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