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\begin{document}

\title{
Role of Information in Physical Sciences 
} 
\author{
Some Examples from Life Sciences
}

\date{}

\maketitle

%\begin{center}
%Wojciech Szpankowski, Purdue University.
%\end{center}
%
\thispagestyle{empty}


%\begin{comment}

%Slide
\stitle{Information and the Sciences -- a Brief History}

\begin{itemize}
\item
Connections between information and the real world have intruigued
researchers for centuries.
\item
Maxwell's thought experiment (circa 1867) in relation to the Second Law
of Thermodynamics provides an elegant nexus.
\centerline{
\psfig{file=maxwell.ps,height=2.3in}
}
\begin{center}
Maxwell's demon was one of the first observations
relating energy to information.
\end{center}
\item
Szilard and Brillouin subsequently used this to equate one bit of information
with $K_BT \ln 2$ joules of energy.
\end{itemize}

\stitle{Information and the Sciences -- a Brief History}

Maxwell's Demon Realized [David Leigh, Nature, 2007]

\centerline{
\psfig{file=leigh.ps,height=4.0in}
}
\begin{center}
Irradiation of rotaxane 1 at 350 nm in CD$_3$OD at 298 K interconverts
the three diastereomers of 1 and, in the presence of benzil, drives the
ring distribution away from the thermodynamic minimum, increasing the
free energy of the molecular system without ever changing the binding
strengths of the macrocycle or ammonium binding sites.
\end{center}


\stitle{Information and the Sciences -- a Brief History}

\begin{itemize}
\item
As the science of information developed, so did interest in correspondence
between information theoretic and scientific measures.
\item
Among the more intuitive and well studied is the correspondence between
thermodynamic (Boltzmann-Gibbs) entropy and information theoretic
(Shannon-Hartley) entropy.
\item
Drawing on these, two questions arise:
\begin{itemize}
\item
Can we draw on information theoretic formalisms to address foundational
questions in scientific disciplines?
\item
Can we draw on physical principles to address basic questions in
computing?
\end{itemize}
\item
This interplay between information and science is the focus of the
proposed institute.
\end{itemize}

%\end{comment}

\stitle{Role of Information in Scientific Discovery: Examples}

{\em What is the ``informative'' component of XRCC1, BRCA-1, and
H. sapiens DNA ligase III?}

\centerline{
\psfig{file=BRCT1.ps,height=4.0in}
}
\begin{center}
BRCT domain, from T.Thermophilus DNA Ligase.
\end{center}

These are inferred using a variety of information correlation and
extraction techniques (sequence analysis, Markov models), and 
experimentally validated.

\stitle{Role of Information in Scientific Discovery: Examples}

{\em What is the ``infomative'' component of a given set of PPI
networks?}

\begin{itemize}
\bigitem{PPI networks for \blue{9 eukaryotic organisms} derived from BIND and DIP}
{\item {\sl A. thaliania, O. sativa, S. cerevisiae, C. elegans, D. melanogaster,
            H. sapiens, B. taurus, M. musculus, R. norvegicus}
 \item \# of \green{proteins} ranges from 288 ({\sl Arabidopsis}) to 8577 ({\sl fruit fly})
 \item \# of \green{interactions} ranges from 340 ({\sl rice}) to 28829 ({\sl fruit fly})
}
\bigitem{Ortholog contraction}
{\item Group proteins according to existing \blue{COG} ortholog clusters
 \item Merge \blue{Homologene} groups into COG clusters
 \item Cluster remaining proteins via \blue{BLASTCLUST}
 \item Ortholog-contracted {\sl fruit fly} network contains 11088 \green{interactions}
 between 2849 \green{ortholog groups}
}

\item {\sc Mule} is available at \\
\blue{\url{http://www.cs.purdue.edu/pdsl/}}
\end{itemize}

\stitle{Conserved Protein Interaction Patterns}

\vspace{1in}
\centerline{
\begin{psfrags}
\scriptsize
\psfrag{Pattern}[c][c]{{\sl Pattern}}
\psfrag{CE}[lt][lt]{{\sl C. elegans}}
\psfrag{SC}[l][l]{{\sl S. cerevisiae}}
\psfrag{DM}[ct][ct]{{\sl D. melanogaster}}
\leavevmode
\epsfig{file=ribon.eps, width=4.5in}
\end{psfrags}
}
\vspace{0.5in}
\centerline{\blue{Small nuclear ribonucleoprotein complex} (\green{$p < 2e-43$})}

\stitle{Conserved Protein Interaction Patterns}

\vspace{1in}
\centerline{
\begin{psfrags}
\scriptsize
\psfrag{Pattern}[c][c]{{\sl Pattern}}
\psfrag{HS}[c][c]{{\sl H. sapiens}}
\psfrag{SC}[c][c]{{\sl S. cerevisiae}}
\psfrag{BT}[c][c]{{\sl B. taurus}}
\leavevmode
\epsfig{file=arp23.eps, width=4.5in}
\end{psfrags}
}
\vspace{0.5in}
\centerline{\blue{Actin-related protein Arp2/3 complex} (\green{$p < 9e-11$})}

\stitle{Conserved Protein Interaction Patterns}

\vspace{1in}
\centerline{
\begin{psfrags}
\scriptsize
\psfrag{Pattern}[c][c]{{\sl Pattern}}
\psfrag{HS}[c][c]{{\sl H. sapiens}}
\psfrag{DM}[c][c]{{\sl S. cerevisiae}}
\psfrag{SC}[l][l]{{\sl D. melanogaster}}
\leavevmode
\epsfig{file=vac.eps, width=6in}
\end{psfrags}
}
\vspace{0.5in}
\centerline{\blue{Endosomal sorting} (\green{$p < 1e-78$})}


\stitle{Role of Information in Scientific Discovery: Examples}

{\em What is the ''informative'' component shared by two given
PPI networks (Yeast and Fruit Fly)?}

\begin{center}
\begin{small}
\begin{tabular}{lcccccc}
\hline\hline
\blue{Rank} & \green{Score} & \red{$z$-score} & \blue{\# Proteins} & \green{\# Matches} & \red{\# Mismatches} & \blue{\# Dups.}\\
\hline\hline
1 & 15.97 & 6.6 & 18 (16, 5) & 28 & 6 & (4, 0)\\
 & \multicolumn{6}{l}{protein amino acid phosphorylation (69\%)}\\
  &  \multicolumn{6}{l}{JAK-STAT cascade (40\%)}\\
\hline
2 & 13.93 & 3.7 & 13 (8, 7) & 25 & 7 & (3, 1)\\
 & \multicolumn{6}{l}{endocytosis (50\%) / calcium-mediated signaling (50\%)}\\
\hline
5 & 8.22 & 13.5 & 9 (5, 3) & 19 & 11 & (1, 0)\\
 & \multicolumn{6}{l}{invasive growth (sensu Saccharomyces) (100\%)}\\
 &  \multicolumn{6}{l}{oxygen and reactive oxygen species metabolism (33\%)}\\
\hline
6 & 8.05 & 7.6 & 8 (5, 3) & 12 & 2 & (0, 1)\\
 & \multicolumn{6}{l}{ubiquitin-dependent protein catabolism (100\%)}\\
 &  \multicolumn{6}{l}{mitosis (67\%)}\\
\hline
21 & 4.36 & 6.2 & 9 (5, 4) & 18 & 13 & (0, 5)\\
 & \multicolumn{6}{l}{cytokinesis (100\%, 50\%)}\\
\hline
30 & 3.76 & 39.6 & 6 (3, 5) & 5 & 1 & (0, 6)\\
 & \multicolumn{6}{l}{DNA replication initiation (100\%, 80\%)}\\
\hline\hline
\end{tabular}
\end{small}
\end{center}

\stitle{Subnets Conserved in Yeast and Fruit Fly}

\vspace{0.5in}
\centerline{Proteosome regulatory particle subnet}
\vspace{0.2in}
\begin{psfrags}
\begin{scriptsize}
\psfrag{SC}[c][c]{{\sl S.Cerevisiae}}
\psfrag{DM}[c][c]{{\sl D.Melanogaster}}
\centerline{\epsfig{file=4932_7227_6.eps, width=5.0in}}
\end{scriptsize}
\end{psfrags}

\vspace{0.5in}
\centerline{Calcium-dependent stress-activated signaling pathway}
\vspace{0.2in}
\begin{psfrags}
\begin{scriptsize}
\psfrag{SC}[c][c]{{\sl S.Cerevisiae}}
\psfrag{DM}[c][c]{{\sl D.Melanogaster}}
\centerline{\epsfig{file=4932_7227_2.eps, width=5.0in}}
\end{scriptsize}
\end{psfrags}


\stitle{Role of Information in Scientific Discovery: Examples}

{\em What are statistically significant functional pathways in
gene regulatory networks?}

\noindent

\href{http://www.cs.purdue.edu/homes/jpandey/narada/}{NARADA DEMO}

\noindent
{\footnotesize
\begin{tabular}{lll}
        \hline
        Frequency & $p$-value & Pathway\\
        \hline
        276 & 5E-94 & metabolic process $\dashv$ flagellum biogenesis $\rightarrow$ transport\\
        136 & 3.1E-71 & regulation of translation $\dashv$ DNA recombination $\rightarrow$ transport\\
        38 & 4.9E-47 & response to stimulus $\dashv$ transcription $\rightarrow$ cell motility\\
        36 & 6.6E-35 & flagellum biogenesis $\rightarrow$ ciliary or flagellar motility\\
        56 & 1.4E-24 & regulation of translation $\dashv$ transcription $\rightarrow$ carboxylic acid metabolism\\
        178 & 8.3E-21 & signal transduction $\dashv$ transcription $\rightarrow$ transport \\
        14 & 8.6E-20 & phosphate transport $\rightarrow$ transcription $\rightarrow$ phosphonate transport\\
        16 & 2E-16 & SOS response $\dashv$ regulation of transcription $\dashv$ DNA repair\\
        501 & 1.2E-13 & regulation of transcription, DNA-dependent $\rightarrow$ transport\\
        12 & 3.6E-10 & proteolysis $\dashv$ regulation of transcription $\dashv$ response to external stimulus \\
        15 & 3.8E-7 & nitrate assimilation $\dashv$ cytochrome complex assembly\\
        10 & 1.4E-6 & cell morphogenesis $\dashv$ protein secretion\\
        178 & 3.8E-4 & transcription $\rightarrow$ carbohydrate metabolic process\\
\hline
\end{tabular}
}



\stitle{Information Sciences in Life Sciences, Ongoing Work}

Characterizing phenotype and disease in networks.

\centerline{\psfig{file=refrence.ps,width=10cm}
            \psfig{file=alzheimers_human.ps,width=13cm}}
\begin{center}
Detecting ``informative'' parts of networks is an essential
aspect of understanding disease and remediation (Alzheimers).
\end{center}


\begin{comment}


\stitle{Using Physical Processes to Solve Problems in Computing: Examples}

DNA Computers

\end{comment}




\end{document}

