CiteULike: jyuh Booth

Data capture in bioinformatics: requirements and experiences with Pedro

Daniel Jameson — 2008-04-10T14:56:42-00:00

BMC Bioinformatics, Vol. 9, No. 1. (2008)

BACKGROUND:The systematic capture of appropriately annotated experimental data is a prerequisite for most bioinformatics analyses. Data capture is required not only for submission of data to public repositories, but also to underpin integrated analysis, archiving, and sharing - both within laboratories and in collaborative projects. The widespread requirement to capture data means that data capture and annotation are taking place at many sites, but the small scale of the literature on tools, techniques and experiences suggests that there is work to be done to identify good practice and reduce duplication of effort.RESULTS:This paper reports on experience gained in the deployment of the Pedro data capture tool in a range of representative bioinformatics applications. The paper makes explicit the requirements that have recurred when capturing data in different contexts, indicates how these requirements are addressed in Pedro, and describes case studies that illustrate where the requirements have arisen in practice. CONCLUSIONS:Data capture is a fundamental activity for bioinformatics; all biological data resources build on some form of data capture activity, and many require a blend of import, analysis and annotation. Recurring requirements in data capture suggest that model-driven architectures can be used to construct data capture infrastructures that can be rapidly configured to meet the needs of individual use cases. We have described how one such model-driven infrastructure, namely Pedro, has been deployed in representative case studies, and discussed the extent to which the model-driven approach has been effective in practice.

Model-based Bayesian clustering (MBBC)

Yongsung Joo — 2008-03-14T03:09:32-00:00

Bioinformatics, Vol. 24, No. 6. (15 March 2008), pp. 874-875.

Motivation: The program MBBC 2.0 clusters timecourse microarray data using a Bayesian product partition model. Results: The Bayesian product partition model in Booth et al. (2007) simultaneously searches for the optimal number of clusters, and assigns cluster memberships based on temporal changes of gene expressions. MBBC 2.0 to makes this method easily available for statisticians and scientists, and is built with three free computer language software packages: Ox, R and C++, taking advantage of the strengths of each language. Within MBBC, the search algorithm is implemented with Ox and resulting graphs are drawn with R. A user-friendly graphical interface is built with C++ to run the Ox and R programs internally. Thus, MBBC users are not required to know how to use Ox, R or C++, but they must be pre-installed. Availability: A self-extractable zip file, MBBC20zip.exe, is available at the MBBC webpage www.stat.ufl.edu/~casella/mbbc/, which contains MBBC.exe, source files, and all other related files. The current version works only in the Windows operating system. A free installation program and overview for Ox is available at www.doornik.com. A detailed installation guide for Ox is provided by MBBC, and is accessible without installing Ox. R is available at www.r-project.org/. Contact: casella@stat.ufl.edu 10.1093/bioinformatics/btn030

Vitamin K and Vitamin D Status: Associations with Inflammatory Markers in the Framingham Offspring Study

Kyla Shea — 2008-02-04T04:05:57-00:00

Am. J. Epidemiol., Vol. 167, No. 3. (1 February 2008), pp. 313-320.

In vitro data suggest protective roles for vitamins K and D in inflammation. To examine associations between vitamins K and D and inflammation in vivo, the authors used multiple linear regression analyses, adjusted for age, sex, body mass index, triglyceride concentrations, use of aspirin, use of lipid-lowering medication, season, menopausal status, and hormone replacement therapy. Participants were from the Framingham Offspring Study (19972001; n = 1,381; mean age = 59 years; 52% women). Vitamin K status, measured by plasma phylloquinone concentration and phylloquinone intake, was inversely associated with circulating inflammatory markers as a group and with several individual inflammatory biomarkers (p < 0.01). Percentage of undercarboxylated osteocalcin, a functional measure of vitamin K status, was not associated with overall inflammation but was associated with C-reactive protein (p < 0.01). Although plasma 25-hydroxyvitamin D was inversely associated with urinary isoprostane concentration, an indicator of oxidative stress (p < 0.01), overall associations between vitamin D status and inflammation were inconsistent. The observation that high vitamin K status was associated with lower concentrations of inflammatory markers suggests that a possible protective role for vitamin K in inflammation merits further investigation. 10.1093/aje/kwm306

Fundamental questions about genes, inactivity, and chronic diseases.

FW Booth — 2007-06-04T03:02:11-00:00

Physiol Genomics, Vol. 28, No. 2. (17 January 2007), pp. 146-157.

Currently our society is faced with the challenge of understanding the biological basis for the epidemics of obesity and many chronic diseases, including Type 2 diabetes. Physical inactivity increases the relative risk of coronary artery disease by 45%, stroke by 60%, hypertension by 30%, and osteoporosis by 59%. Moreover, physical inactivity is cited as an actual cause of chronic disease by the US Centers of Disease Control. Physical activity was obligatory for survival for the Homo genus for hundreds of thousands of years. This review will present evidence that suggests that metabolic pathways selected during the evolution of the human genome are inevitably linked to physical activity. Furthermore, as with many other environmental interactions, cycles of physical activity and inactivity interact with genes resulting in a functional outcome appropriate for the environment. However, as humans are less physically active, there is a maladaptive response that leads to metabolic dysfunction and many chronic diseases. How and why these interactions occur are fundamental questions in biology. Finally, a perspective to future research in physical inactivity-gene interaction is presented. This information is necessary to provide the molecular evidence required to further promote the primary prevention of chronic diseases through physical activity, identify those molecules that will allow early disease detection, and provide society with the molecular information needed to counter the current strategy of adding physical inactivity into our lives.

A chemical proteomics approach to pi3k signaling in macrophages.

Christian Pasquali — 2007-08-26T14:39:54-00:00

Mol Cell Proteomics (7 July 2007)

Prior work employing lipid-based affinity matrices has been used to investigate distinct sets of lipid-binding proteins and one series of experiments has proven successful in mammalian cells for their proteome-wide identification. However, most lipid-based proteomics screens require scaled up sample preparation, are often composed of multiple cell types and are not adapted for simultaneous signal transduction studies. Herein, we provide a chemical proteomics strategy that uses cleavable lipid "baits" with broad applicability to diverse biological samples. The novel baits were designed to avoid preparative steps in order to allow functional proteomics studies when biological source is a limiting factor. This makes this experimental strategy applicable to virtually any primary cell type. Validation of the chemical baits was first confirmed by the selective isolation of several known endogenous PI3K signaling proteins using primary bone marrow-derived macrophages. The use of this technique for cellular proteomics and MS/MS analysis was then demonstrated by the identification of known and potential novel lipid-binding protein, which was confirmed in vitro for several by direct lipid-protein interactions. Further to the identification, the method is also compatible with subsequent signal transduction studies, notably for protein kinase profiling of the isolated lipid-bound protein complexes. Taken together, this integration of minimal scale proteomics, lipid chemistry and activity-based readouts provides a significant advancement in the ability to identify and study the lipid-proteome of single, relevant cell types.

Is this patient dead, vegetative, or severely neurologically impaired? Assessing outcome for comatose survivors of cardiac arrest.

CM Booth — 2006-12-07T14:47:13-00:00

JAMA, Vol. 291, No. 7. (18 February 2004), pp. 870-879.

CONTEXT: Most survivors of cardiac arrest are comatose after resuscitation, and meaningful neurological recovery occurs in a small proportion of cases. Treatment can be lengthy, expensive, and often difficult for families and caregivers. Physical examination is potentially useful in this clinical scenario, and the information obtained may help physicians and families make accurate decisions about treatment and/or withdrawal of care. OBJECTIVE: To determine the precision and accuracy of the clinical examination in predicting poor outcome in post-cardiac arrest coma. DATA SOURCES AND STUDY SELECTION: We searched MEDLINE for English-language articles (1966-2003) using the terms coma, cardiac arrest, prognosis, physical examination, sensitivity and specificity, and observer variation. Other sources came from bibliographies of retrieved articles and physical examination textbooks. Studies were included if they assessed the precision and accuracy of the clinical examination in prognosis of post-cardiac arrest coma in adults. Eleven studies, involving 1914 patients, met our inclusion criteria. DATA EXTRACTION: Two authors independently reviewed each study to determine eligibility, abstract data, and classify methodological quality using predetermined criteria. Disagreement was resolved by consensus. DATA SYNTHESIS: Summary likelihood ratios (LRs) were calculated from random effects models. Five clinical signs were found to strongly predict death or poor neurological outcome: absent corneal reflexes at 24 hours (LR, 12.9; 95% confidence interval [CI], 2.0-68.7), absent pupillary response at 24 hours (LR, 10.2; 95% CI, 1.8-48.6), absent withdrawal response to pain at 24 hours (LR, 4.7; 95% CI, 2.2-9.8), no motor response at 24 hours (LR, 4.9; 95% CI, 1.6-13.0), and no motor response at 72 hours (LR, 9.2; 95% CI, 2.1-49.4). The proportion of individuals' dying or having a poor neurological outcome was calculated by pooling the outcome data from the 11 studies (n = 1914) and used as an estimate of the pretest probability of poor outcome. The random effects estimate of poor outcome was 77% (95% CI, 72%-80%). The highest LR increases the pretest probability of 77% to a posttest probability of 97% (95% CI, 87%-100%). No clinical findings were found to have LRs that strongly predicted good neurological outcome. CONCLUSIONS: Simple physical examination maneuvers strongly predict death or poor outcome in comatose survivors of cardiac arrest. The most useful signs occur at 24 hours after cardiac arrest, and earlier prognosis should not be made by clinical examination alone. These data provide prognostic information, rather than treatment recommendations, which must be made on an individual basis incorporating many other variables.

Does this patient with headache have a migraine or need neuroimaging?

ME Detsky — 2007-07-18T06:33:56-00:00

JAMA, Vol. 296, No. 10. (13 September 2006), pp. 1274-1283.

CONTEXT: In assessing the patient with headache, clinicians are often faced with 2 important questions: Is this headache a migraine? Does this patient require neuroimaging? The diagnosis of migraine can direct therapy, and information obtained from the history and physical examination is used by physicians to determine which patients require neuroimaging. OBJECTIVE: To determine the usefulness of the history and physical examination that distinguish patients with migraine from those with other headache types and that identify those patients who should undergo neuroimaging. DATA SOURCES AND STUDY SELECTION: A systematic review was performed using articles from MEDLINE (1966-November 2005) that assessed the performance characteristics of screening questions in diagnosing migraine (with the International Headache Society diagnostic criteria as a gold standard) and addressed the accuracy of the clinical examination in predicting the presence of underlying intracranial pathology (with computed tomography/magnetic resonance imaging as the reference standard). DATA EXTRACTION: Two authors independently reviewed each study to determine eligibility, abstract data, and classify methodological quality using predetermined criteria. Disagreement was resolved by consensus with a third author. DATA SYNTHESIS: Four studies of screening questions for migraine (n = 1745 patients) and 11 neuroimaging studies (n = 3725 patients) met inclusion criteria. All 4 of the migraine studies illustrated high sensitivity and specificity if 3 or 4 criteria were met. The best predictors can be summarized by the mnemonic POUNDing (Pulsating, duration of 4-72 hOurs, Unilateral, Nausea, Disabling). If 4 of the 5 criteria are met, the likelihood ratio (LR) for definite or possible migraine is 24 (95% confidence interval [CI], 1.5-388); if 3 are met, the LR is 3.5 (95% CI, 1.3-9.2), and if 2 or fewer are met, the LR is 0.41 (95% CI, 0.32-0.52). For the neuroimaging question, several clinical features were found on pooled analysis to predict the presence of a serious intracranial abnormality: cluster-type headache (LR, 10.7; 95% CI, 2.2-52); abnormal findings on neurologic examination (LR, 5.3; 95% CI, 2.4-12); undefined headache (ie, not cluster-, migraine-, or tension-type) (LR, 3.8; 95% CI, 2.0-7.1); headache with aura (LR, 3.2; 95% CI, 1.6-6.6); headache aggravated by exertion or a valsalva-like maneuver (LR, 2.3; 95% CI, 1.4-3.8); and headache with vomiting (LR, 1.8; 95% CI, 1.2-2.6). No clinical features were useful in ruling out significant pathologic conditions. CONCLUSIONS: The presence of 4 simple historical features can accurately diagnose migraine. Several individual clinical features were found to be associated with a significant intracranial abnormality, and patients with these features should undergo neuroimaging.