Biomedical informatics for proteomics.

Mark S Boguski; Martin W McIntosh

doi:10.1038/nature01515

Home/Archive/PubMed

PubMed · 12634797

Biomedical informatics for proteomics.

Mark S Boguski·Martin W McIntosh

View original source ↗Export metadata ↓

Abstract

Success in proteomics depends upon careful study design and high-quality biological samples. Advanced information technologies, and also an ability to use existing knowledge to the full, will be crucial in making sense of the data. Despite its genome-scale potential, proteome analysis is at a much earlier stage of development than genomics and gene expression (microarray) studies. Fundamental issues involving biological variability, pre-analytic factors and analytical reproducibility remain to be resolved. Consequently, the analysis of proteomics data is currently informal and relies heavily on expert opinion. Databases and software tools developed for the analysis of molecular sequences and microarrays are helpful, but are limited owing to the unique attributes of proteomics data and differing research goals.

Explore related subjects

Biomedical Research Computational Biology Databases, Protein Humans Proteins Proteomics Quality Control Reproducibility of Results Research Design Journal Article Review

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Mark S Boguski, Martin W McIntosh. 2003-03-13. Biomedical informatics for proteomics.. https://doi.org/10.1038/nature01515

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Covariates missing by design: comparison of the efficient score to other weighted methods.

This paper addresses the modelling of missing covariate data with the logistic regression model. The aim of this paper is to evaluate the properties of an efficient score for logistic regression in a two-phase design. Simulation studies show that the efficient score is more efficient than two other pseudo-likelihood methods when the correlation between the missing covariate and its surrogate is high or the sampling proportion is small. These methods are illustrated with data from the National Wilms Tumor Study Group. Results from the example confirm the simulation study findings with the exception that the pseudo-likelihood approach produces more reliable estimates than the weighted pseudo-likelihood approach.

Biomedical Research↗

PubMed2007

Tree-based model checking for logistic regression.

A tree procedure is proposed to check the adequacy of a fitted logistic regression model. The proposed method not only makes natural assessment for the logistic model, but also provides clues to amend its lack-of-fit. The resulting tree-augmented logistic model facilitates a refined model with meaningful interpretation. We demonstrate its use via simulation studies and an application to the Pima Indians diabetes data.

Biomedical Research↗

PubMed2007

Evidence-based analysis of physical therapy in Parkinson's disease with recommendations for practice and research.

Physical therapy is often prescribed in Parkinson's disease. To facilitate the uniformity and efficacy of this intervention, we analyzed current evidence and developed practice recommendations. We carried out an evidence-based literature review. The results were supplemented with clinical expertise and patient values and translated into practice recommendations, developed according to international standards for guideline development. A systematic literature search yielded 6 systematic reviews and 23 randomized controlled trials of moderate methodological quality with sufficient data. Six specific core areas for physical therapy were identified: transfers, posture, reaching and grasping, balance, gait, and physical capacity. We extracted four specific treatment recommendations that were based on evidence from more than two controlled trials: cueing strategies to improve gait; cognitive movement strategies to improve transfers; exercises to improve balance; and training of joint mobility and muscle power to improve physical capacity. These practice recommendations provide a basis for current physical therapy in Parkinson's disease in everyday clinical practice, as well as for future research in this field.

Biomedical Research↗