\documentclass[11pt]{article}
\setlength{\oddsidemargin}{0.0truein}
\setlength{\evensidemargin}{0.0truein}
\setlength{\textwidth}{6.5truein}
\setlength{\topmargin}{0.0truein}
\setlength{\textheight}{9.0truein} \setlength{\headsep}{0.0truein}
\setlength{\headheight}{0.0truein} \setlength{\topskip}{10.0pt}
\setlength{\parskip}{5mm}
\usepackage{url}
\usepackage{amsmath}
\usepackage{hyperref}
\usepackage{amssymb}
\pagestyle{empty}
\begin{document}

\begin{center}
  \textbf{\Large{\textsc{STANFORD UNIVERSITY}}}\\[5pt]
  \textbf{\Large{\textsc{DEPARTMENT OF STATISTICS}}}\\[5pt]
  \Large{\textsc{DEPARTMENTAL SEMINAR}}
\end{center}

\begin{center}
  4:15 p.m., Tuesday, April 17, 2007\\
  Sequoia Hall Room 200\\
  (Cookies at 3:45 in 1st Floor Lounge)
\end{center}

\begin{center}
  \textsl{\href{http://www.stat.berkeley.edu/~victor/}{Victor M.~Panaretos}} \\
  Department of Statistics \\
  University of California, Berkeley
\end{center}

\begin{center}
  \subsection*{Random Tomography and Structural Biology}
\end{center}

\noindent Single particle electron microscopy is a powerful method that biophysicists employ to learn about the
structure of biological macromolecules. In contrast to the more traditional crystallographic methods, this
method images “unconstrained” particles, thus posing a variety of statistical problems. We formulate and study
such a problem, one that is essentially of a random tomographic nature, where a structural model for a
biological particle is to be constructed given random projections of its Coulomb potential density, observed
through the electron microscope. Although unidentifiable (ill-posed), this problem can be seen to be amenable to
a statistical solution, once parametric assumptions are imposed. It can also be seen to present challenges both
from a data analysis point of view (e.g. uncertainty estimation and presentation) as well as computationally.
The proposed methodology will be illustrated on simulated data, and practical issues will be discussed.

\end{document}