Biomedical subjects

Mark Craven

Publications and source records attributed to Mark Craven.

3 recordsLinked to original sources

PubMed2003

A Bayesian network approach to operon prediction.

MOTIVATION: In order to understand transcription regulation in a given prokaryotic genome, it is critical to identify operons, the fundamental units of transcription, in such species. While there are a growing number of organisms whose sequence and gene coordinates are known, by and large their operons are not known. RESULTS: We present a probabilistic approach to predicting operons using Bayesian networks. Our approach exploits diverse evidence sources such as sequence and expression data. We evaluate our approach on the Escherichia coli K-12 genome where our results indicate we are able to identify over 78% of its operons at a 10% false positive rate. Also, empirical evaluation using a reduced set of data sources suggests that our approach may have significant value for organisms that do not have as rich of evidence sources as E.coli. AVAILABILITY: Our E.coli K-12 operon predictions are available at http://www.biostat.wisc.edu/gene-regulation.

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PubMed2003

Exposure and sensitization to indoor allergens: association with lung function, bronchial reactivity, and exhaled nitric oxide measures in asthma.

BACKGROUND: Exposure to high levels of allergens in sensitized asthmatic patients causes worsening of pulmonary function in experimental studies. Chronic exposure to lower, naturally occurring levels of allergens might increase the severity of asthma. OBJECTIVE: We sought to study the associations between sensitization and exposure to common indoor allergens (dust mite, cat, and dog) in the home on pulmonary function, exhaled nitric oxide (eNO), and airway reactivity in asthmatic patients. METHODS: Dust samples were collected from the living room carpet and mattress of 311 subject's homes, and Der p 1, Fel d 1, and Can f 1 concentrations were measured by using ELISAs. Spirometry, nonspecific bronchial reactivity, and eNO were measured. RESULTS: Subjects both sensitized and exposed to high levels of sensitizing allergen had significantly lower FEV(1) percent predicted values (mean, 83.7% vs 89.3%; mean difference, 5.6%; 95% CI, 0.6%-10.6%; P =.03), higher eNO values (geometric mean [GM], 12.8 vs 8.7 ppb; GM ratio, 0.7; 95% CI, 0.5-0.8; P =.001), and more severe airways reactivity (PD(20) GM, 0.25 vs 0.73 mg; GM ratio, 2.9; 95% CI, 1.6-5.0; P <.001) compared with subjects not sensitized and exposed. No significant effect of the interaction between sensitization and exposure was found for FEV(1) percent predicted and eNO values. However, there was a significant effect of the interaction between sensitization and exposure to any allergen (P =.05) and between sensitization and exposure to cat allergen (P =.04) for nonspecific bronchial reactivity. CONCLUSION: Asthmatic subjects who are exposed in their homes to allergens to which they are sensitized have a more severe form of the disease.

Adolescent↗

PubMed2003

Predicting bacterial transcription units using sequence and expression data.

MOTIVATION: A key aspect of elucidating gene regulation in bacterial genomes is identifying the basic units of transcription. We present a method, based on probabilistic language models, that we apply to predict operons, promoters and terminators in the genome of Escherichia coli K-12. Our approach has two key properties: (i) it provides a coherent set of predictions for related regulatory elements of various types and (ii) it takes advantage of both DNA sequence and gene expression data, including expression measurements from inter-genic probes. RESULTS: Our experimental results show that we are able to predict operons and localize promoters and terminators with high accuracy. Moreover, our models that use both sequence and expression data are more accurate than those that use only one of these two data sources.

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