The development of technologies to support interpretation of scientific data is a major challenge for bioinformatics. The information explosion within molecular biology has highlighted the difficulties in maintaining scientific models that are consistent--both internally and with the mass of experimental and theoretical data. Even the most experienced biologists struggle with the task of integrating their own observations with the published literature in order to build coherent models. For any complex biological phenomenon, the large number of relevant experimental systems and techniques creates a web of biological knowledge with exponential proportions. It is therefore critical that computational technologies exist for the representation and interpretation of multiple, diverse data sources, and for collaborative scientific interpretation of these data sources. It is further necessary that the next generation of bioinformaticians be trained in the creation and extension of these technologies. The research and education activities proposed here address both these problems. First, we elaborate a research plan to build a prototype for the next generation of structural information resources. The hypothesis of this work is that computer representations of both scientific hypotheses and the primary data upon which they are based, can be used to support multiple activities, including hypothesis formation, hypothesis exploration and hypothesis testing. Second, we elaborate a plan for creating a track within the Stanford medical informatics training program that is specifically geared towards training students in the methods of bioinformatics. Dr. Russ Altman is an Assistant Professor in the Section on Medical Informatics (SMI), within the Department of Medicine at Stanford. He also holds a courtesy appointment in the Department of Computer Science. Dr. Altman was recruited to establish a strong presence of bioinformatics within the SMI, and to focus the traditional stre ngths of the SMI on important problems in basic molecular biology. As such, Dr. Altman has focused on the application of information technology on problems in basic molecular biology. Dr. Altman's goals for this career development award are twofold: 1. The first, research goal, is to create a testbed application for experimenting with the ways in which biologists interact with structural information. This testbed, called RiboWeb, will be an integrated knowledge base about the 16S subunit of the procaryotic ribosome. The knowledge base will contain principled representations of the published structural data and published structural models, and will allow the data and the models to be browsed, evaluated and used for computation. The resource will be made available over the internet, and will provide immediately useful functionality for investigators working on this important structure, as well as allowing students to experiment with new information organization, storage and retrieval technologies, and demonstrate their efficacy empirically. 2. The second, educational goal, is to develop a pathway in bioinformatics at Stanford that provides a general introduction to the field of bioinformatics, and gives students the skills necessary to participate in research in projects such as the test bed application described in the research component. This pathway will leverage the formal coursework in computer science, probability and statistics, biology, and social /ethical issues already provided within the Medical Information Sciences (MIS) PhD/MS program. In addition, this pathway will provide a new course within the MIS training program at Stanford, in which students learn the fundamentals bioinformatics. The unique affiliation with medical informatics will create a population of bioinformaticians who are aware of relevant technologies within other branches of informatics.
