Bruce Schatz - US grants

Professor Schatz is undertaking a one-year investigation to understand and outline the design of a computer system to support an electronic scientific community. While later proposals will be submitted to support the system, this project is to lay the necessary groundwork to enable the implementation to proceed as planned. When implemented, this system should be a new form of biological instrumentation which can effectively manipulate scientific databases. Appropriate community knowledge will be identified to be collected into a digital library and the design will incorporate the systems technology necessary to manipulate this library over nationwide networks. The community chosen is the group of scientists studying the nematode worm Caenorhabditis elegans, a major model organism in molecular biology. The "worm community" consists of some 500 members worldwide, with an unusual degree of open communication and sharing of unpublished information. The community knowledge includes formal data, such as published literature and experimental results, and informal data, such as newsletters and experimental methods. The designed system will capture a significant portion of this knowledge in electronic form and encode it into a "worm information space" which can be transparently browsed by scientists anywhere on nationwide scientific networks. Preparation of the system design requires understanding user needs and available technology. this will be accomplished by working with researchers who will be the system's initial users and who are experts on the available data and technology. Such investigation should enable the design to ensure that the system will contribute to making valuable scientific discoveries.

This research is funded under the Special Initiative on Coordination Theory and Collaboration Technology. This is one of eleven winners under that competition. This project is to develop the systems technology necessary to build a nationwide information infrastructure for the scientific community and to demonstrate this technology by applying it to a mini-collaboratory for a specific community of molecular biologist that studies the genetic structure of the C. Elegans nematode. The goals are to collect the community knowledge into a digital library, develop the technology to manipulate the library, and to learn how to facilitate effective utilization of this technology for sizeable communities. This mini-collaboratory will take advantage of the underlying communication support provided by NSFNET to support users nationwide. The researchers address several research problems necessary to the successful design of the mini-collaboratory. These include designing bulk transfer protocols that facilitate the rapid movement of data across wide area networks, discovering efficient data clustering and caching strategies, providing a uniform interface for displaying editing, searching and grouping a wide range of complex objects, and supporting directory services that can be used to locate many distributed resources.

Neuronal pattern analysis (NPA) documents the dynamic brain processes of sensation, perception, learning and cognition by recording the electrical activity of brain neurons. Recent advances in multi-array recording technologies have greatly expanded the rate at which NPA data can be obtained, and these technologies have fostered means not previously available to study the intercorrelations of dynamic activities in neuronal networks. Computational modeling of brain dynamic activity has fostered major increment in the requirements of data processing due to the need to analyze simulated neuronal spike trains and to compare real and simulated neuronal data. These developments call for parallel development of adequate database systems for organization, rapid access, and sharing of NPA data. This project will establish a database system (DBS) for time series neurophysiological data recorded in experiments of members of the University of Illinois Beckman Institute Neuronal Pattern Analysis Group. System design and implementation will be carried out with consultation and guidance of the National center for Supercomputer Applications. This proposed system will foster community-wide sharing of times series and other forms of neural data, proved a model DBS that can generalize to other neuroscience groups, and enhance the research in the involved laboratories.

This award is for a postdoctoral associate in Experimental Science. The associate, Stella Veretnik, will be working on computational biology from an AI viewpoint.

9319844 Schatz This award will support the distribution and continued development of the Worm Community System (WCS). This is an electronic community system, or digital library, containing the knowledge of a scientific community and a software environment to enable interaction with this knowledge across wide-area networks. In particular, WCS contains the formal and informal data and literature of the community of molecular biologists who study the nematode work C. elegans. The library collection of WCS enables researchers to search for desired items, navigate links between related items, and make personal annotations. This proposal is being jointly supported by the Information Technology and Organizations program of the Directorate for Computer and Information Science and Engineering and by the Database Activities in the Biological Sciences program. ***

This project constructs a digital library testbed and pursues fundamental research addressing the scalable organization of large digital collections. The testbed contains a digital collection containing journals and magazines in the engineering literature in structured SGML format plus pictorial materials obtained from commercial and professional publishers. The associated information systems initially centers about NCSA Mosaic for document display and network access of other resources. Basic research encompasses both technical and social aspects of the testbed capabilities, usage and usage patters including: sociological analysis (including ethnographic observation, surveys and other instruments); economics research over a range of issues. A general goal of the efforts is to enable the design and analysis for digital libraries infrastructure capable of scaling to very large systems.

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This award supports a one-year Japan Society for the Promotion of Science (JSPS) postdoctoral Fellowship for Bruce R. Schatz of the University of Illinois, Urbana-Champaign. He will be undertaking his research with Professor Toru Ishida in the Department of Social Informatics at Kyoto University in Japan. Dr. Schatz will be researching trends in the information infrastructure. He hopes to determine if there are Laws of the Net which predict the behavior of effective algorithms for future technologies of information retrieval. He will be researching the evolution of information infrastructure placing the past, present and future technology in its proper historical context. He will explore the 30-year period from syntactic to structure to semantics. In addition, he will be studying the mass infrastructure for network information systems, such as the 300-year period from 19th century Networks to 20th century Spaces to 21st century Models. He will further explore the philosophical foundations of new technologies for information retrieval in the Net.

The research should result in new paradigms for information technology, with broad impact on the field especially in the area of digital libraries. The exposure of the awardee to a new research setting will be intellectually stimulating. The collaboration should also facilitate further international cooperation in science and technology, and help to facilitate the number of excellent students from the Asian region to the

One of the most important questions in biology is the origin of behavior: nature or nurture? This research will use genomic biology to liberate the study of behavior from the shackles of this dichotomy. The new paradigm is that the environment ("nurture"), which includes other individuals, impacts an inherited genome ("nature") by orchestrating gene expression during the lifetime of the animal. This project will analyze social behavior on an unprecedented whole-genome scale, using Apis mellifera the Western honey bee, as the model organism. Honey bees live in a complex society governed by an age-related division of labor, with each individual assuming many roles during her lifetime. Both genetic heredity and environmental conditions determine what role a bee performs, and when she performs it. The biology research will generate a unique database of gene expressions for all social behavior, recording brain gene expression for hundreds of individuals, each with a specific societal role. These microarray experiments utilize the recently sequenced genome, supported by state-of-the-art statistics. The informatics research will develop an interactive environment to analyze all information sources relevant to bee social behavior. These include genome databases from honey bee and related organisms, linked to complete scientific literature relevant to insect behavior. New text mining technology will integrate molecular description with information from physiology, behavior, neuroscience, and evolution. The BeeSpace environment will enable users to navigate a uniform space of diverse databases and literature sources for hypothesis development and testing. The software system will go beyond a searchable database, using statistical literature analyses to discover functional relationships between genes and behavior. This research will enable all scientists who study bee genes to live on the frontier of integrative biology, where biotechnology enables routine expression analysis and bioinformatics enables functional analysis unconstrained by pre-existing categories.

The broader impact of the interactive environment for functional analysis will be tested in an international community of laboratories studying honey bees and related organisms. Outreach for BeeSpace will provide integrated research and education experiences at the graduate and undergraduate levels, plus training courses and minority outreach at high school and middle school levels.

The workshop brings together a group of scientists with complementary expertise in health informatics, population health, and computer science to identify the research challenges and opportunities in population health data measurement, representation, and predictive modeling.

Despite great advances in measurement, computing, and communication technologies, the health data measurement relies on legacy practices (e.g., phone surveys). In contrast, billions of persons worldwide have mobile devices, such as cell phones and music players, which contain measurement sensors and are increasingly network aware. If these devices could be appropriately employed for population health data measurement, they could revolutionize the acquisition and use of population health data. However, there are many research challenges that need to be addressed in order to make widespread use of actionable population health data.

The workshop is organized around a vision of actionable data for population health. It covers a broad range of questions such as: What data should be recorded to measure everyday health? How should this data be most helpfully collected? How should the sensor data be classified into actionable data? How should the diverse sources be judged for quality? How should this data be mined and correlated? How can population data be transformed into usable knowledge? How should this data be used to develop practical health systems? How can multiple knowledge sources be integrated for multiple users? How can existing data (medical records and clinical trials) be leveraged using model-based inference to support customized decision making and refine predictive models? What is the impact of this new data on health quality and cost?

Workshop participants include experts in the areas of health informatics, knowledge representation and inference, machine learning and data mining. Thw workshop aims to increase the awareness of research challenges and opportunities in health informatics in general, and population data measurement, representation, and predictive modeling in particular, among researchers in data mining, knowledge representation and inference, machine learning, text analysis, human-computer interaction, social networks and social media, semantic web, decision theory. It also aims to make researchers in health informatics, public health, and related areas better aware of the state of the art informatics approaches that could be leveraged to develop the next generation health informatics infrastructure. The workshop results, including new research challenges and opportunities in discovery informatics, will be broadly disseminated through the workshop report, publications by workshop participants, and outreach efforts through follow-up activities that engage the research community.