On the biophysics front, Dr, Elber's Research Group is interested in computational algorithms to extend the time scale of simulations in molecular biophysics. Straightforward simulation techniques allow the exploration of nanosecond processes. This is much shorter than the microsecond and millisecond time scales of protein folding, channel activation, and allosteric transitions of proteins. All are critical processes of living cells. The Group works to develop methods for global optimization of approximate trajectories and pathways for qualitative analysis of long-time mechanisms in molecular biophysics. Recently they have also developed a quantitative non-Markovian theory (milestoning) that extracts information from short-time dynamics and allows the calculation of longtime biologically relevant processes. Their ideas, theories, and algorithms are summarized in the software package MOIL. On the bioinformatics front they develop machine-learning approaches to model protein structures from sequences (summarized in our web server LOOPP). The Group also use these techniques to investigate the network of sequence flow between protein structures and propose a novel picture of protein space that suggests sequence migration between distinct three dimensional shapes, a finding with significant relevance to protein design and evolution.