The US Department of Energy has formed a collaboration of researchers that it has tasked with developing a systems biology database that will enable comparative genomics research for scientists studying plants, microbes, and the environment. DOE's Office of Science recently announced that the team, which includes Hope College's Matthew DeJongh, Associate Professor of Computer Science and Aaron Best, Associate Professor of Biology, and is spread across eight institutions around the country, will work together to develop the Systems Biology Knowledgebase, which is designed to enhance collaborative computational research.

Initiated with $3 million in funding from the 2009 American Recovery and Reinvestment Act, the Knowledgebase project will provide new capabilities for researchers to evaluate data-driven theories of microbial and plant systems and to generate new data, protocols, algorithms, and testable models.

The first round of funding supported development of a mapping strategy, architecture, and pilot software projects for the database.

The DOE's Office of Science 2012 budget request to Congress seeks $12 million to fund the build-out of the Knowledgebase, which will include extensive software development, data capture, and integration efforts.

"Hidden in the mountains of biology data we are accumulating today are the secrets of Nature's solutions to a broad range of challenges we face in energy and the environment," said Sharlene Weatherwax, DOE's associate director of science for biological and environmental research (BER). "The Knowledgebase will accelerate our ability to unlock those secrets and help take systems biology to a new level."

Funded through BER's Genomic Science division, the Knowledgebase will use capabilities and supercomputing facilities within the DOE's national lab complex including the Joint Genome Institute, the BioEnergy Scientific Computing Center at Lawrence Berkeley National Laboratory, the Magellan testbed, and other DOE facilities.

The Knowledgebase project will be led by principal investigator Adam Arkin, director of the Physical Biosciences Division of the Lawrence Berkeley National Lab.

The Computer Science department's summer research program is set to begin on May 31, 2011. This summer program is in its 20th year and has been funded by the National Science Foundation for each of those years. This summer, we will have 15 students involved: 10 from Hope College and 5 from off-campus.

This summer, our four faculty members will be joined by Ravi Agarwal, a faculty member from St. Norbert's College in Depree, Wisconsin.

Our research will focus on six different areas:

1. Chuck Cusack will conduct one team on a project called "Algorithms for Graph Pebbling". The project will involve developing and testing algorithms for graph pebbling problems.
2. Chuck Cusack will also conduct a team on another project, called "Human Computing Games for Graph Problems". This project attempts to inform the automated solution of graph problems by learning from how humans play computing games.
3. Matt DeJongh will be working on a project entitled "Modeling Bacterial Metabolism and Genetic Regulation" This project intertwines biology, computer science, and mathematics students and faculty in interdisciplinary research in systems biology. The goal of systems biology is to build computer models that use genetic information about an organism to simulate and predict its behavior.
4. Mike Jipping will be conducting a team working on "Assistive Technology with Android on Mobile Phones" This project will use the technology of Android mobile phones to assist people with visual impairment.
5. Ryan McFall will be working a a project called "Building an online survey system" with a team. This project will involve continuing development, testing and deployment of a free, open source software system to administer and analyze online surveys, similar to services such as SurveyMonkey.
6. Ravi Agarwal will be working with his team on a project called "Android Robotics: Android makes Robots Smarter". This project will explore possibilities of using an Android powered device attached to a robot to control and navigate the robot.
   

New software developed with the involvement of faculty and student researchers at Hope College is helping to speed dramatically the time-intensive, painstaking task of transforming the immense amount of genomic data being collected worldwide into working models of how organisms function at a fundamental level. Professor Matt DeJongh in the Computer Science department, and student Paul Frybarger (middle), contributed to the development and publication of the Model SEED, a web-based resource for the automatic generation, optimization and refinement of microbial metabolic models. The work was recently highlighted in an article published in the August issue of the prestigious monthly scientific journal "Nature Biotechnology." In 2009, the journal ranked first in biotechnology and applied microbiology for its "impact factor" - a measure of the frequency with which the publication's articles are cited elsewhere - as determined by Thomson Reuters Journal Citation Reports.

According to Hope faculty members Dr. Aaron Best (Biology Department) and DeJongh, co-leaders of the Hope research team, the web-based "Model SEED" resource, which is available at http://www.theseed.org/models, can reduce to 48 hours most of the calculations that used to take a year to render manually - and the research team is working on speeding up the rest. Even as the Model SEED is already being used by scientists internationally, they noted that the team is also looking at a further step: how to use the models in examining a variety of questions, from the way that some bacteria cause diseases to how other bacteria produce energy and clean up pollution.

The resource reflects collaboration between researchers at Argonne National Laboratory - where Model SEED is based - the University of Chicago and Hope. The "Nature Biotechnology" article's six co-authors, representing the three institutions on the research team, include three from Hope: DeJongh, who is an associate professor of computer science; Best, an associate professor of biology; and recent graduate Paul Frybarger, who worked on the project as a student. Lead author is Christopher S. Henry of Argonne National Laboratory and the University of Chicago; the other authors, Ben Linsay and Rick L. Stevens, are both with the University of Chicago as well.

DeJongh noted that the impetus for the Model SEED grew from the reality that the tools for working with genomic information haven't kept up with the explosion in data collection made possible by advances in biotechnology.

"The capability of generating data has been outpacing the ability to analyze it, so we've needed software to analyze this genome-level data," he said. "That's where the tools that we've created come in."

"This kind of work used to take a person about a year to do on a manual basis," DeJongh said. "We can effectively do 80 to 90 percent of that work in 48 hours now, and we're working on tools to assist scientists doing that remaining 10 to 20 percent by hand."

Combined, the speed and analytical capabilities are an important new tool, Best explained.

"A particularly valuable outcome of this work is that the software provides a powerful framework for comparing how different organisms perform certain functions or respond to conditions. This is a framework that has been lacking," he said. "A resource like this allows researchers to, for instance, look at two very closely related strains of bacteria--one that causes disease, another that doesn't - and better understand the differences in how they function."

The Model SEED is accessible to researchers around the globe through the RAST (Rapid Annotation using Subsystems Technology) genome analysis service available through Argonne National Laboratory. The SEED project is a nationwide, open-source effort to develop and share genomic data.

Best and DeJongh and Hope students have been working on the project for about five years. In addition to receiving National Science Foundation (NSF) grant support for their work, Best and DeJongh both received Towsley Research Scholar awards from Hope and funding from a multi-purpose Howard Hughes Medical Institute grant to Hope.

In developing and testing the Model SEED, the research team generated 130 models of a variety of forms of bacteria - life forms that involve thousands of distinct biochemical processes. Subsequent comparison of the models with real-life data has found the system to be 87 percent accurate.

"It is remarkable that this level of agreement between model and experimental data is achieved with little manual input into the model-building process and for a very diverse group of bacteria," Best said. "As researchers begin to focus in on models for individual bacteria, not only will this accuracy increase, but the models have the potential to reveal and predict important behaviors that will help us understand how these bacteria interact with their environment."

The overall effort is currently supported by two major grants from the NSF. The first, awarded to Best and DeJongh in 2008, has supported the development of the models and modeling software, and will continue through this spring as the team seeks to automate some of the remaining analysis. The other, a two-year award that Best and DeJongh received with colleague Dr. Nathan Tintle of the mathematics faculty, is supporting taking the simulation further, from creating a model that accurately reflects the systems being represented to using the model to see how the systems respond to different situations.

"The new grant builds on this resource to use these models to analyze other kinds of data," DeJongh said. "What can we get out of it when we start feeding it environmental data and make simulations and statistical predictions?"

Professors and students in the Computer Science department are engaged in a new software development project. This project combines online survey creation with the Google Web Toolkit in an extra-curricular learning opportunity that will go on for the entire semester.

For this project, students and professors work on teams that are learning and extending an existing -- but uncompleted -- project. The survey software is was written by Dr. McFall several years ago and is used for several purposes on campus, include the online teaching evaluations and student congress elections. Dr. McFall and Dr. Jipping have been working together to redevelop the software from its current state (written primarily in Perl and running on a Sybase database) to a more Web 2.0 version, written primarily in Java using a technology called the Google Web Toolkit (GWT). Teams meet for about an hour and a half on Friday afternoons.

This project is one of several others that the department has conducted over the last several years. In the past, we have developed software that has extended the functionality of TV recording software and has implemented new features in teaching software used by the Communications department. All experience ranges are encouraged to work on this project -- from both students and professors! Teams are mixed to consist of all experience levels. All participants are broadening their knowledge of software development techniques and tools.

And there is free food!

This project is expected to go on all semester and should significantly extend and refine the online survey software.