The use of biological data in addition to the carcinogen bioassay in quantitative risk assessment.
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BUILD is a program generator acting at source code level. The generated code corresponds to a whole application in order to model a biological process of interest using an iterative adjustment of experimental data. The program is designed to be executed in command line mode for processing of multiple data files with an individual execution control for each file. The results are completed by modular statistical and graphical functions. This approach has been shown to reduce the time and the amount of work needed for program development, debugging and maintenance. To date, BUILD has been successfully used in mathematical analysis of phenomenological approaches, but other fields of activity, such as educational software, are also conceivable.
OBJECTIVE: We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis regulation. METHODS: We cast both models and background knowledge in terms of processes that interact to account for behavior. We also describe IPM, an algorithm for inducing quantitative process models from such input. RESULTS: We demonstrate IPM's use both on photosynthesis and on a second domain, biochemical kinetics, reporting the models induced and their fit to observations. CONCLUSION: We consider the generality of our approach, discuss related research on biological modeling, and suggest directions for future work.
As the number, richness and diversity of biological sources grow, scientists are increasingly confronted with the problem of selecting appropriate sources and tools. To address this problem, we have designed BioGuidel, a user-centric framework that helps scientists choose sources and tools according to their preferences and strategy, by specifying queries through a user-friendly visual interface. In this paper, we provide a complete RDF representation of BioGuide and introduce XPR (eXtensible Path language for RDF), an extension of FSL2 that is expressive enough to model all BioGuide queries. BioGuide queries modeled as XPR expressions can then be saved, compared, evaluated and exchanged through the Web between users and applications.
The goal in designing beam-modulating devices for heavy charged-particle therapy is to achieve uniform biological effects across the spread-peak region of the beam. To accomplish this, the linear-quadratic model for cell survival has been used to describe the biological response of the target cells to charged-particle radiation. In this paper, the sensitivity of the beam-modulator design in the high-dose region to the values of the linear-quadratic variables alpha and beta has been investigated for a 215-MeV/u helium beam, and implications for higher LET beams are discussed. The major conclusions of this work are that, for helium over the LET range of 2 to 16 keV/mu, uncertainties in measuring alpha and beta for a given cell type which are of the order of 20% or less have a negligible effect on the beam-modulator design (i.e., on the slope of the spread Bragg peak); uncertainties less than or equal to 10% in the dose-averaged LET at each depth are unimportant; and, if the linear-quadratic variables for the tumor differ from those used in the beam-modulator design by a constant factor between about 0.5 and 3, then the resultant nonuniformity in the photon-equivalent dose delivered to the tumor is within +/- 25%. It is also shown that for any ion, if the nominal values of alpha or beta used by the beam-modulator design program differ from their actual values by a constant factor, then the maximum errors possible in the beam-modulator design may be characterized by two limiting depth-dose curves such that the ratio of the dose at the proximal end of the spread Bragg curve to the dose at the distal end of the spread peak is given by alpha distal/alpha prox for the steepest curve, and square root of beta distal/beta prox for the flattest curve.
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Waves have long been thought to be a fundamental mechanism for communicating information within a medium and are widely observed in biological systems. However, a quantitative analysis of biological waves is confounded by the variability and complexity of the response. This paper proposes a robust technique for extracting wave structure from experimental data by calculating "wave subspaces" from the KL decomposition of the data set. If a wave subspace contains a substantial portion of the data set energy during a particular time interval, one can deduce the structure of the wave and potentially isolate its information content. This paper uses the wave subspace technique to extract and compare wave structure in data from three different preparations of the turtle visual cortex. The paper demonstrates that wave subspace caricatures from the three cortical preparations have qualitative similarities. In the numerical model, where information about the underlying dynamics is available, wave subspace landmarks are related to activation and changes in behavior of other dynamic variables besides membrane potential.
Physiological parameters of laboratory animals used for biomedical research is crucial for following several experimental procedures. With the intent to establish baseline biologic parameters for non-human primates held in closed colonies, hematological and morphometric data of captive monkeys were determined. Data of clinically healthy rhesus macaques (Macaca mulatta), cynomolgus monkeys (Macaca fascicularis), and squirrel monkeys (Saimiri sciureus) were collected over a period of five years. Animals were separated according to sex and divided into five age groups. Hematological data were compared with those in the literature by Student's t test. Discrepancies with significance levels of 0.1, 1 or 5% were found in the hematological studies. Growth curves showed that the sexual dimorphism of rhesus monkeys appeared at an age of four years. In earlier ages, the differences between sexes could not be distinguished (p < 0.05). Sexual dimorphism in both squirrel monkeys and cynomolgus monkeys occurred at an age of about 32 months. Data presented in this paper could be useful for comparative studies using primates under similar conditions.
The BCM Search Launcher is an integrated set of World Wide Web (WWW) pages that organize molecular biology-related search and analysis services available on the WWW by function, and provide a single point of entry for related searches. The Protein Sequence Search Page, for example, provides a single sequence entry form for submitting sequences to WWW servers that offer remote access to a variety of different protein sequence search tools, including BLAST, FASTA, Smith-Waterman, BEAUTY, PROSITE, and BLOCKS searches. Other Launch pages provide access to (1) nucleic acid sequence searches, (2) multiple and pair-wise sequence alignments, (3) gene feature searches, (4) protein secondary structure prediction, and (5) miscellaneous sequence utilities (e.g., six-frame translation). The BCM Search Launcher also provides a mechanism to extend the utility of other WWW services by adding supplementary hypertext links to results returned by remote servers. For example, links to the NCBI's Entrez data base and to the Sequence Retrieval System (SRS) are added to search results returned by the NCBI's WWW BLAST server. These links provide easy access to auxiliary information, such as Medline abstracts, that can be extremely helpful when analyzing BLAST data base hits. For new or infrequent users of sequence data base search tools, we have preset the default search parameters to provide the most informative first-pass sequence analysis possible. We have also developed a batch client interface for Unix and Macintosh computers that allows multiple input sequences to be searched automatically as a background task, with the results returned as individual HTML documents directly to the user's system. The BCM Search Launcher and batch client are available on the WWW at URL http:@gc.bcm.tmc.edu:8088/search-launcher.html.
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The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.
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Scientific data of importance to biologists reside in a number of different data sources, such as GenBank, GSDB, SWISS-PROT, EMBL, and OMIM, among many others. Some of these data sources are conventional databases implemented using database management systems (DBMSs) and others are structured files maintained in a number of different formats (e.g., ASN.1 and ACE). In addition, software packages such as sequence analysis packages (e.g., BLAST and FASTA) produce data and can therefore be viewed as data sources. To counter the increasing dispersion and heterogeneity of data, different approaches to integrating these data sources are appearing throughout the bioinformatics community. This paper surveys the technical challenges to integration, classifies the approaches, and critiques the available tools and methodologies.
New advances in automated cytology, computer microscopy, densitometry and other instrumentation for feature/scene acquisition or analysis have resulted in higher information densities than heretofore encountered. Two-, three- and four-space computer graphics provide favorable bandwidth conditions for transforming complex, large-scale data sets into visual displays that allow a human observer, utilizing the brain's efficient processing of visual information, to rapidly grasp relationships and synthesize concepts. Examples of multidimensional displays are presented, all developed by neuroscientists who are not computer specialists. Because modern graphics and image-synthesis techniques can now be implemented on any one of several commercially available very-high-speed integrated-circuit-based display systems, at moderate cost, exploitation of specifically visual presentation should be carefully considered in any system generating information in high density.
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