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J Schug

Publications and source records attributed to J Schug.

9 recordsLinked to original sources
PubMed2001

A relational schema for both array-based and SAGE gene expression experiments.

MOTIVATION AND RESULTS: A relational schema is described for capturing highly parallel gene expression experiments using different technologies. This schema grew out of efforts to build a database for collaborators working on different biological systems and using different types of platforms in their gene expression experiments as well as different types of image quantification software. The tables are conceptually organized into three categories of information: Platform, Experiment (which includes image scanning and quantification), and Data. The strengths of the schema are: (i) integrating information on array elements using a gene index; (ii) describing samples using ontologies; (iii) reducing an experiment to a single RNA source for precise descriptions yet not losing the relationships between experiments done at the same time or for the same project; and (iv) maintaining both raw and processed (e.g. cleansed and normalized) data and recording how the data is processed. The result is a novel schema, which can hold both array and non-array data, is extensible for detailed experimental descriptions that are precise and consistent, and allows for meaningful comparisons of genes between experiments.

Databases, Factual↗
PubMed2001

High-resolution BAC-based map of the central portion of mouse chromosome 5.

The current strategy for sequencing the mouse genome involves the combination of a whole-genome shotgun approach with clone-based sequencing. High-resolution physical maps will provide a foundation for assembling contiguous segments of sequence. We have established a bacterial artificial chromosome (BAC)-based map of a 5-Mb region on mouse Chromosome 5, encompassing three gene families: receptor tyrosine kinases (PdgfraKit-Kdr), nonreceptor protein-tyrosine type kinases (Tec-Txk), and type-A receptors for the neurotransmitter GABA (Gabra2, Gabrb1, Gabrg1, and Gabra4). The construction of a BAC contig was initiated by hybridization screening the C57BL/6J (RPCI-23) BAC library, using known genes and sequence tagged sites (STSs). Additional overlapping clones were identified by searching the database of available restriction fingerprints for the RPCI-23 and RPCI-24 libraries. This effort resulted in the selection of >600 BAC clones, 251 kb of BAC-end sequences, and the placement of 40 known and/or predicted genes within this 5-Mb region. We use this high-resolution map to illustrate the integration of the BAC fingerprint map with a radiation-hybrid map via assembled expressed sequence tags (ESTs). From annotation of three representative BAC clones we demonstrate that up to 98% of the draft sequence for each contig could be ordered and oriented using known genes, BAC ends, consensus sequences for transcript assemblies, and comparisons with orthologous human sequence. For functional studies, annotation of sequence fragments as they are assembled into 50-200-kb stretches will be remarkably valuable.

Animals↗
PubMed1998

GAIA: framework annotation of genomic sequence.

As increasing amounts of genomic sequence from many organisms become available, and as DNA sequences become a primary reagent in biologic investigations, the role of annotation as a prospective guide for laboratory experiments will expand rapidly. Here we describe a process of high-throughput, reliable annotation, called framework annotation, which is designed to provide a foundation for initial biologic characterization of previously unexamined sequence. To examine this concept in practice, we have constructed Genome Annotation and Information Analysis (GAIA), a prototype software architecture that implements several elements important for framework annotation. The center of GAIA consists of an annotation database and the associated data management subsystem that forms the software bus along which other components communicate. The schema for this database defines three principal concepts: (1) Entries, consisting of sequence and associated historical data; (2) Features, comprising information of biologic interest; and (3) Experiments, describing the evidence that supports Features. The database permits tracking of annotation results over time, as well as assessment of the reliability of particular results. New framework annotation is produced by CARTA, a set of autonomous sensors that perform automatic analyses and assert results into the annotation database. These results are available via a Web-based query interface that uses graphical Java applets as well as text-based HTML pages to display data at different levels of resolution and permit interactive exploration of annotation. We present results for initial application of framework annotation to a set of test sequences, demonstrating its effectiveness in providing a starting point for biologic investigation, and discuss ways in which the current prototype can be improved. The prototype is available for public use and comment at http://www.cbil.upenn.edu/gaia.

Amino Acid Sequence↗
PubMed1998

The GAIA software framework for genome annotation.

We describe a software framework, GAIA, that supports semi-automated annotation of uncharacterized sequence data. The annotation framework incorporates annotation by data source integration, data analysis, and manual data entry. Components of the system include a configurable, open data analysis pipeline, a relational information storage manager, and Java-based graphical user interfaces. We discuss design decisions and tradeoffs in building such a system, and policies and strategies for producing consistent, uniform, high quality annotation.

Base Sequence↗
PubMed1997

Grinding precision and accuracy of fit of CEREC 2 CAD-CIM inlays.

The authors conducted research to determine the grinding precision and accuracy of fit of ceramic inlays generated with the completely redesigned CEREC 2 computer-assisted design/computer-integrated manufacturing, or CAD-CIM, unit. They found that the grinding precision of the CEREC 2 unit was 2.4 times greater than that of CEREC 1. With CEREC 2, the mean (+/-standard deviation) luting interfaces were 56 +/- 27 micrometers, which is a 30 percent improvement in the accuracy of fit compared with that of CEREC 1.

Computer-Aided Design↗
PubMed1997

Modeling transcription factor binding sites with Gibbs Sampling and Minimum Description Length encoding.

Transcription factors, proteins required for the regulation of gene expression, recognize and bind short stretches of DNA on the order of 4 to 10 bases in length. In general, each factor recognizes a family of "similar" sequences rather than a single unique sequence. Ultimately, the transcriptional state of a gene is determined by the cooperative interaction of several bound factors. We have developed a method using Gibbs Sampling and the Minimum Description Length principle for automatically and reliably creating weight matrix models of binding sites from a database (TRANSFAC) of known binding site sequences. Determining the relationship between sequence and binding affinity for a particular factor is an important first step in predicting whether a given uncharacterized sequence is part of a promoter site or other control region. Here we describe the foundation for the methods we will use to develop weight matrix models for transcription factor binding sites.

Algorithms↗
PubMed1995

[Grinding precision and accuracy of the fit of Cerec-2 CAD/CIM inlays].

The grinding precision of one Cerec-1 (C1) and one Cerec-2 (C2) CAD/CIM unit each was evaluated using standardized inlay-like (mod) samples (n = 40) of Vita Cerec Mk II porcelain and Dicor MGC glass ceramic. Typical dimensions (B, E, F, H) of the sampleS were measured and the standard deviations (SD) analysed statistically using the F-test. SD of C2-machined sample dimensions were significantly lower using both Vita, B: p < 0.05; E: p < 0.001; F: p < 0.001; H: p < 0.001, and Dicor MGC, B: p < 0.05; E: p < 0.001; F: p < 0.001; H: p < 0.01, than those machined with C1, indicating a strong improvement of grinding precision of C2 compared to C1. Accuracy of fit to human molar cavities of mod inlays machined with C1 (n = 6) and C2 (n = 6) was evaluated using a scanning electron microscope with 100x magnification. The width of the interfacial luting gap was generally lower in C2 inlays (56 +/- 27 microns) than with C1 (84 +/- 38 microns). Significant differences (t-test) were seen in margin sections "cervical line angles above CEJ" (C1 = 124 +/- 44/C2 = 59 +/- 30 microns, p < 0.05), "cervical line angles at CEJ" (C1 = 109 +/- 55/C2 = 67 +/- 27 microns, p < 0.05) and "gingival margin above CEJ" (C1 = 81 +/- 32 microns/C2 = 31 +/- 18 microns, p < 0.05).

Ceramics↗