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Selected Projects in Bioinformatics
Collaborative
Molecular Modeling Environment
Peter Kuhn, The Scripps Research Institute, U.S.
A modern day
collaborative lab environment often entails research that involves
use of widely different types of data like gel-pictures,
purification chromatograms, mass spectrometry, diffraction images,
tabulated cloning results, literature references, etc. We describe a
new application that enables the bench scientist to quickly attach
annotations to a 3-D structure or 2-D image. These annotations are
stored in a SQL Server database managed by the Office SharePoint
Server which provides features such as document versioning and
organization. A researcher can quickly create a site for a project,
choose an image or 3-D structure as the contextual basis and begin
annotating in minutes. Other authorized users can immediately see
the new annotations which can be browsed, sorted, edited and added
to, spurring discussion and a flow of ideas.
The need to
collaborate in a multi-domain networked lab environment requires the
ability to share diverse types of data with several users but on a
common context. The C-ME application provides a shared context (PDB
structure or 2-D image) on which annotations may be placed
presenting additional information to the protein structure or
microscope image.
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Computational Tools for
Population Biology
Tanya Berger-Wolf, University of Illinois at Chicago, U.S.
The goal of this
research is to develop algorithmic tools that will allow biologist
to exploit the imminent, widespread availability of sensor-derived
data in order to find connections between ecology and behavior and
behavior and social processes. Our approach is to combine ideas
from social network analysis, internet computing, distributed
computing, and graph algorithm design to solve problems in
population biology, both animal and human (e.g., epidemiology). We
focus on the dynamic aspects of social interactions and develop
computational tools that address the time component of interactions
explicitly.
Our goal is to
develop a novel conceptual framework to accurately describe the
social context of an individual at time scales matching changes in
individual and group activity. Existing theory, both for analysis of
social and other pairwise interaction networks (such as WWW,
internet, cellphones), is based on identifying trends that develop
over long periods of time. Such a static theory is too crude for
determining the linkage between social context and the emergence of
fine-grained individual or group behavior.
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Microsoft
Research Support for iGEM
Randy Rettberg, Massachusetts Institute of Technology, U.S.
Synthetic Biology
lies at a junction between engineering and biology, with a research
goal to learn how to best design and build engineered biological
systems. Our education goal is to enable all interested students to
participate directly in the work of learning how to engineer
biology.
iGEM started as a
month-long design class at MIT in 2003 and 2004. With NSF support, 5
schools participated in a design competition over the summer of
2004. With Microsoft iCampus support, iGEM grew to 13 schools in
2005.
In 2006,
thirty-seven student teams from schools in Asia, Europe, Latin
America, Africa, and the US have been specifying, designing,
building, and testing biological systems made from standard,
interchangeable biological parts. The students are highly motivated
to build, to design, and to compete. In the process, biology
students learn approaches for organizing complex systems and
practical tools for design, modeling, and simulation while
engineering students are able to immerse themselves in biology.
The impact of iGEM
extends beyond the students, energizing biological curricula at the
participating schools, changing the attitudes of instructors and
professors towards active biology education and the emerging field
of Synthetic Biology. Several of the iGEM schools taught special
classes in Synthetic Biology in the spring in order to be ready for
the summer competition, and MIT is just one of the schools to add a
Synthetic Biology module from iGEM to the undergraduate biological
engineering lab.
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SQL Server-based
Comparative Analysis of RNA Sequences, Structures, & Evolution
Robin Gutell, University of Texas at Austin, U,S.
Our understanding
of the structure, function, and evolution of RNA molecules has
increased significantly with recent improvements in sequencing and
crystallography. The accuracy and detail that can be deciphered from
RNA data is directly proportional to the creativity, design and
speed of the analysis as well the organization and accessibility of
the data.
The amount of
sequence and structure data has increased by orders of magnitude
over the years and the objectives of analysis have become more
ambitious and sophisticated. We are now developing a new computer
system using SQLServer 2005 which will integrate more than 500,000
sequences and associated structural and phylogenetic information
into a database for hosting analysis and ad-hoc data retrieval
tasks.
Our goal is to
perform the majority of the analysis within SQLServer, including
sequence alignment, covariation analysis and other types of
statistical and phylogenetic queries using TSQL and CLR stored
procedures. Preliminary work has demonstrated that this concept is
fully functional.
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