Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

3.10 - Nitroxide-Mediated Polymerization

This Review describes the application of nitroxides to synthesis and polymer chemistry. The synthesis and physical properties of nitroxides are discussed first. The largest section focuses on their application as stoichiometric and catalytic oxidants in organic synthesis. The oxidation of alcohols and carbanions, as well as oxidative C-C bond-forming reactions are presented along with other typical oxidative transformations. A section is also dedicated to the extensive use of nitroxides as trapping reagents for C-centered radicals in radical chemistry. Alkoxyamines derived from nitroxides are shown to be highly useful precursors of C-centered radicals in synthesis and also in polymer chemistry. The last section discusses the basics of nitroxide-mediated radical polymerization (NMP) and also highlights new developments in the synthesis of complex polymer architectures.

Nitroxides: applications in synthesis and in polymer chemistry.

Since its introduction in the early 1990s, nitroxide-mediated radical polymerization (NMP) has been widely adopted for the preparation of a panoply of new polymer architectures. While NMP provides a number of advantages for the preparation of specific types of polymers, several inherent limitations with NMP have led to the more widespread use of other reversible-deactivation radical polymerization (RDRP) methods, chiefly atom transfer radical polymerization (ATRP) and reversible addition-fragmentation-chain transfer (RAFT) polymerization, in polymer synthesis. This short review discusses strategies that have been adopted for dealing with the difficulties of NMP and also surveys the use of NMP to prepare new polymers and copolymers over the past several years.

Nitroxide-Mediated Radical Polymerization: Limitations and Versatility

Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

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Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Data sharing anchors reproducible science, but expectations and best practices are often nebulous. Communities of funders, researchers and publishers continue to grapple with what should be required or encouraged. To illuminate the rationales for sharing data, the technical challenges and the social and cultural challenges, we consider the stakeholders in the scientific enterprise. In biomedical research, participants are key among those stakeholders. Ethical sharing requires considering both the value of research efforts and the privacy costs for participants. We discuss current best practices for various types of genomic data, as well as opportunities to promote ethical data sharing that accelerates science by aligning incentives.

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Responsible, practical genomic data sharing that accelerates research.

In order to expand the utility of current polymeric micellar systems, we have developed amphiphilic multiblock copolymers containing alternating blocks of poly(acrylic acid) and poly(styrene). Heterotelechelic poly(tert-butyl acrylate-b-styrene) diblock copolymers containing an α-alkyne and an ω-azide were synthesized by atom transfer radical polymerization (ATRP), allowing control over the molecular weight while maintaining narrow polydispersity indices. The multiblock copolymers were constructed by copper-catalyzed azide-alkyne cycloaddition of azide−alkyne end functional diblock copolymers which were then characterized by 1H NMR, FT-IR and SEC. The tert-butyl moieties of the poly(tert-butyl acrylate-b-styrene) multiblock copolymers were easily removed to form the poly(acrylic acid-b-styrene) multiblock copolymer ((PAA−PS)9), which contained up to 9 diblock repeats. The amphiphilic multiblock (PAA−PS)9 (Mn = 73.3 kg/mol) was self-assembled by dissolution into tetrahydrofuran and extensive dialysis again...

Poly(Acrylic Acid-b-Styrene) Amphiphilic Multiblock Copolymers as Building Blocks for the Assembly of Discrete Nanoparticles.

The N-phenylalkoxyamine N-(1-methyl-(1-(4-nitrophenoxy)carbonyl)ethoxy)-N-(1-methyl-(1-(4-nitrophenoxy)carbonyl)ethyl)benzenamine (1) was prepared by the addition of 4-nitrophenyl 2-methylpropionat-2-yl radicals across the double bond of nitrosobenzene and evaluated as an initiator for nitroxide-mediated polymerization (NMP). N-Phenylalkoxyamines have not been extensively studied in NMP, though they have shown promise in controlling methyl methacrylate (MMA) polymerization to moderate conversions. It is thought that delocalization of the nitroxide radical through the N-phenyl substituent may minimize cross-disproportionation of the nitroxide with the chain end that has made NMP of MMA difficult. Here, we show that alkoxyamine 1 is capable of controlling the NMP of MMA to 50% conversion while maintaining narrow molecular weight distributions (Mw/Mn = 1.12−1.30). Additionally, chain extension from the resulting PMMA macroinitiators with MMA or styrene allows the formation of diblock copolymers. The correspo...

Nitroxide-Mediated Polymerization of Methyl Methacrylate and Styrene with New Alkoxyamines from 4-Nitrophenyl 2-Methylpropionat-2-yl Radicals

Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs.

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Anna C. Greene

Papers

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Responsible, practical genomic data sharing that accelerates research.

Poly(Acrylic Acid-b-Styrene) Amphiphilic Multiblock Copolymers as Building Blocks for the Assembly of Discrete Nanoparticles.

Nitroxide-Mediated Polymerization of Methyl Methacrylate and Styrene with New Alkoxyamines from 4-Nitrophenyl 2-Methylpropionat-2-yl Radicals

Adapting bioinformatics curricula for big data