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David Page

Publications and source records attributed to David Page.

14 recordsLinked to original sources
PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗
PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g., associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available at https://bioconductor.org/packages/MPAC, enables similar multi-omic analyses on new datasets.

Journal Article↗
PubMed2006

Precancer: a conceptual working definition -- results of a Consensus Conference.

BACKGROUND: Precancers are lesions that precede the appearance of invasive cancers. The successful prevention or treatment of precancers has the potential to eliminate deaths due to cancer. METHODS: A National Cancer Institute-sponsored Conference on Precancer was convened on November 8-9, 2004, at The George Washington University Medical Center, Washington, DC. A definition of precancers was developed over 2 days of Conference discussions. RESULTS: The following five criteria define a precancer: (1) evidence must exist that the precancer is associated with an increased risk of cancer; (2) when a precancer progresses to cancer, the resulting cancer arises from cells within the precancer; (3) a precancer differs from the normal tissue from which it arises; (4) a precancer differs from the cancer into which it develops, although it has some, but not all, of the molecular and phenotypic properties that characterize the cancer; (5) there is a method by which the precancer can be diagnosed. CONCLUSIONS: The Conference participants developed a general definition for precancers that would provide a consistent and clinically useful way of distinguishing precancers from all other types of lesions. It was recognized that many precancerous lesions may not meet this strict definition, but the group felt it was necessary to define criteria that will help standardize clinical and biological studies. Furthermore, a set of defining criteria for putative precancer lesions will permit pathologists to build a diagnostically useful taxonomy of precancers based on specified clinical and biological properties. Precancers thus characterized can be classified into clinically relevant sub-groups based on shared properties (i.e. biomarkers, oncogenes, common metabolic pathways, responses to therapy, etc.). Publications that introduce newly described precancer entities should describe how each of the five defining criteria apply. This manuscript reviews the proposed definition of precancers and suggests how pathologists, oncologists and cancer researchers may determine when these criteria are satisfied.

Humans↗
PubMed2006

Experimental design of time series data for learning from dynamic Bayesian networks.

Bayesian networks (BNs) and dynamic Bayesian networks (DBNs) are becoming more widely used as a way to learn various types of networks, including cellular signaling networks, from high-throughput data. Due to the high cost of performing experiments, we are interested in developing an experimental design for time series data generation. Specifically, we are interested in determining properties of time series data that make them more efficient for DBN modeling. We present a theoretical analysis on the ability of DBNs without hidden variables to learn from proteomic time series data. The analysis reveals, among other lessons, that under a reasonable set of assumptions a fixed budget is better spent on collecting many short time series data than on a few long time series data.

Algorithms↗
PubMed2005

Evidence from the Mars Express High Resolution Stereo Camera for a frozen sea close to Mars' equator.

It is thought that the Cerberus Fossae fissures on Mars were the source of both lava and water floods two to ten million years ago. Evidence for the resulting lava plains has been identified in eastern Elysium, but seas and lakes from these fissures and previous water flooding events were presumed to have evaporated and sublimed away. Here we present High Resolution Stereo Camera images from the European Space Agency Mars Express spacecraft that indicate that such lakes may still exist. We infer that the evidence is consistent with a frozen body of water, with surface pack-ice, around 5 degrees north latitude and 150 degrees east longitude in southern Elysium. The frozen lake measures about 800 x 900 km in lateral extent and may be up to 45 metres deep--similar in size and depth to the North Sea. From crater counts, we determined its age to be 5 +/- 2 million years old. If our interpretation is confirmed, this is a place that might preserve evidence of primitive life, if it has ever developed on Mars.

Exobiology↗
PubMed2005

Shigellosis among swimmers in a freshwater lake.

OBJECTIVE: Shigella infection is highly communicable; however, outbreaks associated with swimming in recreational fresh water are rarely identified. MATERIALS AND METHODS: A cohort study of lake visitors was performed. RESULTS: Seventeen (24.6%) case patients among 69 persons who visited the lake over the holiday weekend were identified. Attack rates increased with increasing exposure to lake water; the risk of illness was greatest among swimmers who reported getting lake water in their mouths (relative risk = 5.37, 95% confidence interval = 2.2, 13.3). Shigella sonnei was isolated from stool samples of four of eight swimmers tested. CONCLUSIONS: The outbreak likely was caused by fecal contamination of lake water by an infected swimmer; there was no evidence of sewage contamination into the lake. Fresh water is a potential source of infection in patients with acute gastroenteritis and recent exposure. Since testing and chlorination of lake water is impractical, prevention relies on avoidance of fecal contamination and/or minimizing ingestion of the water.

Adolescent↗
PubMed2005

Knowledge discovery from structured mammography reports using inductive logic programming.

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

Algorithms↗
PubMed2004

Lsm proteins promote regeneration of pre-mRNA splicing activity.

Lsm proteins are ubiquitous, multifunctional proteins that affect the processing of most RNAs in eukaryotic cells, but their function is unknown. A complex of seven Lsm proteins, Lsm2-8, associates with the U6 small nuclear RNA (snRNA) that is a component of spliceosome complexes in which pre-mRNA splicing occurs. Spliceosomes contain five snRNAs, U1, U2, U4, U5, and U6, that are packaged as ribonucleoprotein particles (snRNPs). U4 and U6 snRNAs contain extensive sequence complementarity and interact to form U4/U6 di-snRNPs. U4/U6 di-snRNPs associate with U5 snRNPs to form U4/U6.U5 tri-snRNPs prior to spliceosome assembly. Within spliceosomes, disruption of base-paired U4/U6 heterodimer allows U6 snRNA to form part of the catalytic center. Following completion of the splicing reaction, snRNPs must be recycled for subsequent rounds of splicing, although little is known about this process. Here we present evidence that regeneration of splicing activity in vitro is dependent on Lsm proteins. RNP reconstitution experiments with exogenous U6 RNA show that Lsm proteins promote the formation of U6-containing complexes and suggest that Lsm proteins have a chaperone-like function, supporting the assembly or remodeling of RNP complexes involved in splicing. Such a function could explain the involvement of Lsm proteins in a wide variety of RNA processing pathways.

Multigene Family↗
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.

Algorithms↗
PubMed2003

Histopathology of breast cancer among African-American women.

Although the overall incidence of breast cancer in African-American women is lower than in white women, African-American women younger than 50 years old have a higher incidence of breast cancer than white women. African-American women with breast cancer have a poorer survival rate than white women and are more likely to die of breast cancer in almost every age group. To explain this disparity, we studied a substantial body of literature that reported a biologic difference in the tumors found in African-American and white women. Specifically, more aggressive histopathologic patterns have been described among African-American patients with breast cancer when compared with white women. In addition, there are data that support an ethnicity-related variation in the expression of breast tumor hormonal markers. The objective of this study was to critically evaluate the existing published data on the histologic features of breast cancer to determine whether breast cancer in African-American women is a histologically more aggressive disease than in white women. We conclude that the aggressive tumor histology reported in African-American women has not been analyzed carefully with respect to the age of the patient at the time of diagnosis and the stage of disease at presentation. Furthermore, there is a need for central pathology review using accepted, published criteria for diagnosis of uncommon and controversial histologic subtypes of breast cancer.

Adult↗
PubMed2002

Modelling regulatory pathways in E. coli from time series expression profiles.

MOTIVATION: Cells continuously reprogram their gene expression network as they move through the cell cycle or sense changes in their environment. In order to understand the regulation of cells, time series expression profiles provide a more complete picture than single time point expression profiles. Few analysis techniques, however, are well suited to modelling such time series data. RESULTS: We describe an approach that naturally handles time series data with the capabilities of modelling causality, feedback loops, and environmental or hidden variables using a Dynamic Bayesian network. We also present a novel way of combining prior biological knowledge and current observations to improve the quality of analysis and to model interactions between sets of genes rather than individual genes. Our approach is evaluated on time series expression data measured in response to physiological changes that affect tryptophan metabolism in E. coli. Results indicate that this approach is capable of finding correlations between sets of related genes.

Adaptation, Physiological↗
PubMed2002

Factors influencing immunization status in primary care clinics.

BACKGROUND AND OBJECTIVES: National standards and goals for childhood immunization rates are well established. Yet, despite clear standards and goals, physicians do not achieve the desired rate (90%) for immunization coverage. This study examined factors related to immunization status for 2-year-old children in pediatric and family practice settings. METHODS: Specially trained personnel used computer software to audit 2,552 records from 42 practices in Northeast Florida throughout 1997-1999. Immunization records were judged as either complete or incomplete, and factors related to immunization status were studied. Clinic type and 18 immunization practice standards were reviewed for effect on immunization status. RESULTS: The probability of complete immunization status for children in pediatric clinics was greater than for those in family practice clinics. Multivariate logistic regression revealed that use of semiannual audits (odds ratio [OR]=2.00, confidence interval [CI]=1.65-2.42) was the most important factor for immunization completion. This was followed by availability of discounted immunizations (OR=.44, CI=.27-.73) and the use of an immunization tracking system (OR= 1.48, CI= 1.18-1.70). Factors that were not found to contribute included clinic type and the remaining 15 practice standards. CONCLUSIONS: Considering the significant factors, immunization status was not affected by the type of clinic providing immunizations. Based on this analysis, family physicians should implement tracking systems and should perform semiannual audits to match the success of pediatricians in immunizing children. Neither group met nationally established goals for administration of immunizations for 2-year-old children.

Child Health Services↗