1,450 research outputs found
Some recent biological discoveries in Hawai'i, photographed alive
Western Region, National Park Servic
The Platelet as a Model for Chemical Genetics
AbstractChemical genetics is an emerging strategy in chemical biology that promises to bring the power of true genetics to mammalian systems and facilitate the transfer of biological discoveries to therapeutics. The platelet is an anucleate cell with several features that render it suitable for chemical genetic analysis. This review addresses the benefits and challenges of chemical genetics using platelets as a model system
RIBAR and xRIBAR: methods for reproducible relative MS/MS-based label-free protein quantification
Mass spectrometry-driven proteomics is increasingly relying on quantitative analyses for biological discoveries. As a result, different methods and algorithms have been developed to perform relative or absolute quantification based on mass spectrometry data. One of the most popular quantification methods are the so-called label-free approaches, which require no special sample processing, and can even be applied retroactively to existing data sets. Of these label-free methods, the MS/MS-based approaches are most often applied, mainly because of their inherent simplicity as compared to MS-based methods. The main application of these approaches is the determination of relative protein amounts between different samples, expressed as protein ratios. However, as we demonstrate here, there are some issues with the reproducibility across replicates of these protein ratio sets obtained from the various, MS/MS-based label-free methods, indicating that the existing methods are not optimally robust. We therefore present two new Methods (called RIBAR and xRIBAR) that use the available MS/MS data more effectively, achieving increased robustness. Both the accuracy and the precision of our novel methods are analyzed and compared to the existing methods to illustrate the increased robustness of our new methods over existing ones
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation
Clinical Pharmacology & Therapeutics: Past, Present, and Future.
Clinical Pharmacology & Therapeutics (CPT), the definitive and timely source for advances in human therapeutics, transcends the drug discovery, development, regulation, and utilization continuum to catalyze, evolve, and disseminate discipline-transformative knowledge. Prioritized themes and multidisciplinary content drive the science and practice of clinical pharmacology, offering a trusted point of reference. An authoritative herald across global communities, CPT is a timeless information vehicle at the vanguard of discovery, translation, and application ushering therapeutic innovation into modern healthcare
Alignment-free local structural search by writhe decomposition
Motivation: Rapid methods for protein structure search enable biological discoveries based on flexibly defined structural similarity, unleashing the power of the ever greater number of solved protein structures. Projection methods show promise for the development of fast structural database search solutions. Projection methods map a structure to a point in a high-dimensional space and compare two structures by measuring distance between their projected points. These methods offer a tremendous increase in speed over residue-level structural alignment methods. However, current projection methods are not practical, partly because they are unable to identify local similarities
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