DoerLBH / Paper

Interesting Papers for later

2016-05-14 posted in [Paper]

doi:10.1126/science.aad7701 PMC: PMID:

Single-molecule decoding of combinatorially modified nucleosomes

Efrat Shema1,2, Daniel Jones3, Noam Shoresh2, Laura Donohue1,2, Oren Ram1,2, Bradley E. Bernstein1,2,*

Different combinations of histone modifications have been proposed to signal distinct gene regulatory functions, but this area is poorly addressed by existing technologies. We applied high-throughput single-molecule imaging to decode combinatorial modifications on millions of individual nucleosomes from pluripotent stem cells and lineage-committed cells. We identified definitively bivalent nucleosomes with concomitant repressive and activating marks, as well as other combinatorial modification states whose prevalence varies with developmental potency. We showed that genetic and chemical perturbations of chromatin enzymes preferentially affect nucleosomes harboring specific modification states. Last, we combined this proteomic platform with single-molecule DNA sequencing technology to simultaneously determine the modification states and genomic positions of individual nucleosomes. This single-molecule technology has the potential to address fundamental questions in chromatin biology and epigenetic regulation.

http://science.sciencemag.org/content/352/6286/717


doi:10.1126/science.aad8036 PMC: PMID:

Design of structurally distinct proteins using strategies inspired by evolution

T. M. Jacobs1, B. Williams2, T. Williams2, X. Xu3,4,*, A. Eletsky3,4, J. F. Federizon3, T. Szyperski3, B. Kuhlman2,5,†

Natural recombination combines pieces of preexisting proteins to create new tertiary structures and functions. We describe a computational protocol, called SEWING, which is inspired by this process and builds new proteins from connected or disconnected pieces of existing structures. Helical proteins designed with SEWING contain structural features absent from other de novo designed proteins and, in some cases, remain folded at more than 100°C. High-resolution structures of the designed proteins CA01 and DA05R1 were solved by x-ray crystallography (2.2 angstrom resolution) and nuclear magnetic resonance, respectively, and there was excellent agreement with the design models. This method provides a new strategy to rapidly create large numbers of diverse and designable protein scaffolds.

http://science.sciencemag.org/content/352/6286/687


Nature 533, 73–76 (05 May 2016) doi:10.1038/nature17439

Machine-learning-assisted materials discovery using failed experiments

Paul Raccuglia, Katherine C. Elbert, Philip D. F. Adler, Casey Falk, Malia B. Wenny, Aurelio Mollo, Matthias Zeller, Sorelle A. Friedler, Joshua Schrier & Alexander J. Norquist

Inorganic–organic hybrid materials1, 2, 3 such as organically templated metal oxides1, metal–organic frameworks (MOFs)2 and organohalide perovskites4 have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table5, 6, 7, 8, 9. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative10) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility11, photovoltaic properties12, gas adsorption capacity13 or lithium-ion intercalation14) to identify promising target candidates for synthetic efforts11, 15; determination of the structure–property relationship from large bodies of experimental data16, 17, enabled by integration with high-throughput synthesis and measurement tools18; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification19, 20 or gas adsorption properties21). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on ‘dark’ reactions—failed or unsuccessful hydrothermal syntheses—collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted conditions for new organically templated inorganic product formation with a success rate of 89 per cent. Inverting the machine-learning model reveals new hypotheses regarding the conditions for successful product formation.

http://www.nature.com/nature/journal/v533/n7601/full/nature17439.html

Paper - Characterizing the transmission dynamics and control of ebola virus disease

2016-03-12 posted in [Paper]

Chowell, G. & Nishiura, H. Characterizing the transmission dynamics and control of ebola virus disease. PLoS Biol 13, e1002057, doi:10.1371/journal.pbio.1002057 (2015).

Paper - Inference and forecast of the current west african ebola outbreak in Guinea, sierra leone and liberia

2016-03-11 posted in [Paper]

Shaman, J., Yang, W. & Kandula, S. Inference and forecast of the current west african ebola outbreak in Guinea, sierra leone and liberia. PLoS Curr 6, doi:10.1371/currents.outbreaks.3408774290b1a0f2dd7cae877c8b8ff6 (2014).

Paper - Early transmission dynamics of Ebola virus disease (EVD), West Africa, March to August 2014

2016-03-10 posted in [Paper]

Nishiura, H. & Chowell, G. Early transmission dynamics of Ebola virus disease (EVD), West Africa, March to August 2014. Euro Surveill 19 (2014).

Paper - Dynamics and control of Ebola virus transmission in Montserrado, Liberia - a mathematical modeling analysis

2016-03-09 posted in [Paper]

Lewnard, J. A. et al. Dynamics and control of Ebola virus transmission in Montserrado, Liberia: a mathematical modelling analysis. Lancet Infect Dis 14, 1189-1195, doi:10.1016/S1473-3099(14)70995-8 (2014).

Paper - Thermodynamic and kinetic analysis of sensitivity amplification in biological signal transduction

2016-03-07 posted in [Paper]

Qian, H. Thermodynamic and kinetic analysis of sensitivity amplification in biological signal transduction. Biophys Chem 105, 585-593 (2003).

Paper - How to escape the cancer attractor - Rationale and limitations of multi-target drugs

2016-03-06 posted in [Paper]

Huang, S. & Kauffman, S. How to escape the cancer attractor: Rationale and limitations of multi-target drugs. Seminars in Cancer Biology 23, 270-278, doi:http://dx.doi.org/10.1016/j.semcancer.2013.06.003 (2013).

Paper - Transmission dynamics and control of Ebola virus disease (EVD) - a review

2016-03-05 posted in [Paper]

Chowell, G. & Nishiura, H. Transmission dynamics and control of Ebola virus disease (EVD): a review. BMC Med 12, 196, doi:10.1186/s12916-014-0196-0 (2014).

Paper - An IDEA for short term outbreak projection - nearcasting using the basic reproduction number

2016-03-04 posted in [Paper]

Fisman, D. N., Hauck, T. S., Tuite, A. R. & Greer, A. L. An IDEA for short term outbreak projection: nearcasting using the basic reproduction number. PLoS One 8, e83622, doi:10.1371/journal.pone.0083622 (2013).

Paper - The basic reproductive number of Ebola and the effects of public health measures - the cases of Congo and Uganda

2016-03-03 posted in [Paper]

Paper - Poincaré, celestial mechanics, dynamical-systems theory and “chaos”

2016-03-02 posted in [Paper]

Paper - Experimental and Modeling Study of Oscillations in the Chlorine Dioxide Iodine Malonic-Acid Reaction

2016-03-01 posted in [Paper]

Paper - Combining flux and energy balance analysis to model large-scale biochemical networks

2016-02-29 posted in [Paper]

Paper - Generalized Haldane equation and fluctuation theorem in the steady-state cycle kinetics of single enzymes

2016-02-28 posted in [Paper]

Paper - Linear analysis near a steady-state of biochemical networks (control analysis, correlation metrics and circuit theory)

2016-02-27 posted in [Paper]

Paper - The chemical master equation approach to nonequilibrium steady-state of open biochemical systems

2016-02-26 posted in [Paper]

Paper - Stochastic phenotype transition of a single cell in an intermediate region of gene state switching

2016-02-25 posted in [Paper]

Paper - Anticipating critical transitions

2016-02-24 posted in [Paper]

Paper - Universal resilience patterns in complex networks

2016-02-23 posted in [Paper]

Launch "A Paper A Day" Plan

2016-02-22 posted in [Paper]