The thermal unimolecular decomposition of HCO: effects of state specific rate constants on the thermal rate constantElectronic supplementary information (ESI) available: Experimental data and conditions. See http://www.rsc.org/suppdata/cp/b4/b402139h/

2004 ◽  
Vol 6 (13) ◽  
pp. 3383 ◽  
Author(s):  
Horst Hippler ◽  
Nikolina Krasteva ◽  
Frank Striebel
Keyword(s):  
Experimental Data ◽  
Rate Constants ◽  
Supplementary Information ◽  
Specific Rate ◽  
Unimolecular Decomposition

Mechanodestruction of Isoprene Rubber. Part 1. Process Kinetics

2021 ◽  
Vol 80 (3) ◽  
pp. 118-122
Author(s):  
V.P. Dorozhkin ◽  
◽  
E.G. Mokhnatkina ◽  
D.N. Zemsky ◽  
A.D. Valiev ◽  
...  
Keyword(s):  
Experimental Data ◽  
Molecular Mass ◽  
Rate Constants ◽  
Oxidative Destruction ◽  
Process Kinetics ◽  
Mass Fractions ◽  
Rubber Part ◽  
Kinetics Of ◽  
Selection Of ◽  
Isoprene Rubber

A method is proposed that allows us to obtain the values of the rate constants (CR) of the processes of mechanodestruction (mechanical cracking) of kм, oxidative destruction of kо, and recombination of kр macromolecules, as well as the mass fractions of the corresponding fractions of φм, φо, and φр,r involved in the plasticization process (P) of SKI-3 isoprene rubber. The method is based on the selection of the values of these parameters that correspond to the previously obtained experimental data, using the previously obtained recurrent equations and a specially developed program. The dependences of the CR on the time P at 30oC are obtained, which allows us to describe the kinetics of the processes accompanying P at this temperature, and the changes in molecular mass (MM) in this process. It is shown that constant values of CR are established at large times of P. Refined explanations of the nature of the kinetics of the CR change at P are proposed. The MM value of SKI-3 macromolecules that have not undergone destruction is calculated, depending on the time of plasticization.

scholarly journals Haplotype assembly of autotetraploid potato using integer linear programing

2019 ◽  
Vol 35 (18) ◽  
pp. 3279-3286 ◽  
Author(s):  
Enrico Siragusa ◽  
Niina Haiminen ◽  
Richard Finkers ◽  
Richard Visser ◽  
Laxmi Parida
Keyword(s):  
Experimental Data ◽  
Experimental Studies ◽  
Simulated Data ◽  
Supplementary Information ◽  
Linear Programs ◽  
Plant Genomics ◽  
Optimal Method ◽  
Haplotype Assembly ◽  
Open Issue ◽  
Removal Model

Abstract Summary Haplotype assembly of polyploids is an open issue in plant genomics. Recent experimental studies on highly heterozygous autotetraploid potato have shown that available methods do not deliver satisfying results in practice. We propose an optimal method to assemble haplotypes of highly heterozygous polyploids from Illumina short-sequencing reads. Our method is based on a generalization of the existing minimum fragment removal model to the polyploid case and on new integer linear programs to reconstruct optimal haplotypes. We validate our methods experimentally by means of a combined evaluation on simulated and experimental data based on 83 previously sequenced autotetraploid potato cultivars. Results on simulated data show that our methods produce highly accurate haplotype assemblies, while results on experimental data confirm a sensible improvement over the state of the art. Availability and implementation Executables for Linux at http://github.com/Computational Genomics/HaplotypeAssembler. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Modeling cell proliferation in human acute myeloid leukemia xenografts

2019 ◽  
Vol 35 (18) ◽  
pp. 3378-3386 ◽  
Author(s):  
Marco S Nobile ◽  
Thalia Vlachou ◽  
Simone Spolaor ◽  
Daniela Bossi ◽  
Paolo Cazzaniga ◽  
...  
Keyword(s):  
Experimental Data ◽  
Cell Proliferation ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Time Series Data ◽  
Supplementary Information ◽  
Series Data ◽  
Proliferative Potential ◽  
Proliferating Cells ◽  
Acute Myeloid

Abstract Motivation Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often complex to achieve. To overcome these limitations, model-driven approaches can be exploited to investigate different aspects of cell population dynamics. Results In this work, we present ProCell, a novel modeling and simulation framework to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events. We apply ProCell to compare different models of cell proliferation in AML, notably leveraging experimental data derived from human xenografts in mice. ProCell is coupled with Fuzzy Self-Tuning Particle Swarm Optimization, a swarm-intelligence settings-free algorithm used to automatically infer the models parameterizations. Our results provide new insights on the intricate organization of AML cells with highly heterogeneous proliferative potential, highlighting the important role played by quiescent cells and proliferating cells characterized by different rates of division in the progression and evolution of the disease, thus hinting at the necessity to further characterize tumor cell subpopulations. Availability and implementation The source code of ProCell and the experimental data used in this work are available under the GPL 2.0 license on GITHUB at the following URL: https://github.com/aresio/ProCell. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals HypercubeME: two hundred million combinatorially complete datasets from a single experiment

2019 ◽  
Author(s):  
Laura Avino Esteban ◽  
Lyubov R Lonishin ◽  
Daniil Bobrovskiy ◽  
Gregory Leleytner ◽  
Natalya S Bogatyreva ◽  
...  
Keyword(s):  
Experimental Data ◽  
High Throughput ◽  
Recursive Algorithm ◽  
Random Mutagenesis ◽  
Higher Order ◽  
Supplementary Information ◽  
Single Experiment ◽  
Manual Curation ◽  
Complete Dataset ◽  
Genotype Space

Abstract Motivation Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a “combinatorially complete dataset”. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. Results We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199,847,053 unique combinatorially complete genotype combinations of dimensionality ranging from two to twelve. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data. Availability https://github.com/ivankovlab/HypercubeME.git Supplementary information Supplementary data are available at Bioinformatics online.

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