Exact quantum quasiclassical, and semiclassical reaction probabilities for the collinear F+D_2 → FD+D reaction

Exact quantum, quasiclassical, and semiclassical reaction probabilities and rate constants for the collinear reaction F+D_2 → FD+D are presented. In all calculations, a high degree of population inversion is predicted with P^R_(03) and P^R(04) being the dominant reaction probabilities. In analogy with the F+H_2 reaction (preceding paper), the exact quantum 0→3 and 0→4 probabilities show markedly different energy dependence with PR03 having a much smaller effective threshold energy (E_T=0.014 eV) than P^R_(04) (0.055 eV). The corresponding quasiclassical forward probabilities P^R_(03) and P^R_(04) are in poor agreement with the exact quantum ones, while their quasiclassical reverse and semiclassical counterparts provide much better approximations to the exact results. Similar comparisons are also made in the analysis of the corresponding EQ, QCF, QCR, and USC rate constants. An information theoretic analysis of the EQ and QCF reaction probabilities indicates nonlinear surprisal behavior as well as a significant isotope dependence. Additional quantum results at higher energies are presented and discussed in terms of threshold behavior and resonances. Exact quantum reaction probabilities for the related F+HD → FH+D and F+DH → FD+H reactions are given and an attempt to explain the observed isotope effects is made

Large quantum effects in the collinear F+H2-->FH+H reaction

We have performed accurate quantum mechanical calculations of reaction probabilities for the collinear F+H2-->FH+H reaction as well as corresponding quasiclassical trajectory calculations. A comparison of these results shows that very significant quantum mechanical effects are present in this reaction

Biological data sciences in genome research

The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution. Incredibly, as we look into the future over the next 20 years, we see the very real potential for sequencing more than 1 billion genomes, bringing even deeper insight into human genetics as well as the genetics of millions of other species on the planet. Realizing this great potential for medicine and biology, though, will only be achieved through the integration and development of highly scalable computational and quantitative approaches that can keep pace with the rapid improvements to biotechnology. In this perspective, I aim to chart out these future technologies, anticipate the major themes of research, and call out the challenges ahead. One of the largest shifts will be in the training used to prepare the class of 2035 for their highly interdisciplinary world

Computational thinking in the era of big data biology

It is fall again, and another class of students has arrived in the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (CSHL). Building on the lab's 100-year history as a leading center for research and education, the Watson School was established in 1998 as a graduate program in biology with a focus on molecular, cellular and structural biology, and neuroscience, cancer, plant biology and genetics. All students in the program complete the same courses, centered around these research topics, with an emphasis on the principles of scientific reasoning and logic, as well as the importance of ethics and effective communication. Three years ago the curriculum was expanded to include a new course on quantitative biology (QB) and I, along with my co-instructor Mickey Atwal and other members of the QB program, have been teaching it ever since

The Influence of Reaction Rates on the Final p-Abundances

The astrophysical p-process is responsible for the origin of the proton rich nuclei,which are heavier than iron. A huge network involving thousands of reaction rates is necessary to calculate the final p-abundances. But not all rates included in the network have a strong influence on the p-nuclei abundances. The p-process was investigated using a full nuclear reaction network for a type II supernovae explosion when the shock front passes through the O/Ne layer. Calculations were done with a multi-layer model adopting the seed of a pre-explosion evolution of a 25 mass star. In extensive simulations we investigated the impact of single reaction rates on the final p-abundances. The results are important for the strategy of future experiments in this field.Comment: 4 page

Genomic dark matter: the reliability of short read mapping illustrated by the genome mappability score

Motivation: Genome resequencing and short read mapping are two of the primary tools of genomics and are used for many important applications. The current state-of-the-art in mapping uses the quality values and mapping quality scores to evaluate the reliability of the mapping. These attributes, however, are assigned to individual reads and do not directly measure the problematic repeats across the genome. Here, we present the Genome Mappability Score (GMS) as a novel measure of the complexity of resequencing a genome. The GMS is a weighted probability that any read could be unambiguously mapped to a given position and thus measures the overall composition of the genome itself. Results: We have developed the Genome Mappability Analyzer to compute the GMS of every position in a genome. It leverages the parallelism of cloud computing to analyze large genomes, and enabled us to identify the 5-14% of the human, mouse, fly and yeast genomes that are difficult to analyze with short reads. We examined the accuracy of the widely used BWA/SAMtools polymorphism discovery pipeline in the context of the GMS, and found discovery errors are dominated by false negatives, especially in regions with poor GMS. These errors are fundamental to the mapping process and cannot be overcome by increasing coverage. As such, the GMS should be considered in every resequencing project to pinpoint the 'dark matter' of the genome, including of known clinically relevant variations in these regions

Metassembler: merging and optimizing de novo genome assemblies

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. We apply it to the four genomes from the Assemblathon competitions and show it consistently and substantially improves the contiguity and quality of each assembly. We also develop guidelines for meta-assembly by systematically evaluating 120 permutations of merging the top 5 assemblies of the first Assemblathon competition. The software is open-source at http://metassembler.sourceforge.net

Proton Drip-Line Calculations and the Rp-process

One-proton and two-proton separation energies are calculated for proton-rich nuclei in the region $A=41-75$. The method is based on Skyrme Hartree-Fock calculations of Coulomb displacement energies of mirror nuclei in combination with the experimental masses of the neutron-rich nuclei. The implications for the proton drip line and the astrophysical rp-process are discussed. This is done within the framework of a detailed analysis of the sensitivity of rp process calculations in type I X-ray burst models on nuclear masses. We find that the remaining mass uncertainties, in particular for some nuclei with $N=Z$, still lead to large uncertainties in calculations of X-ray burst light curves. Further experimental or theoretical improvements of nuclear mass data are necessary before observed X-ray burst light curves can be used to obtain quantitative constraints on ignition conditions and neutron star properties. We identify a list of nuclei for which improved mass data would be most important.Comment: 20 pages, 9 figures, 2 table

The reactions and ashes of thermonuclear explosions on neutron stars

This paper reports on the detailed rp-process reaction flow on an accreting neutron star and the resulting ashes of a type I X-ray burst. It is obtained by coupling a 298 isotope reaction network to a self-consistent one-dimensional model calculation with a constant accretion rate of dM/dt=1.0e17g/s (0.09 Eddington).Comment: 4 pages, 2 figures, submitted to the INPC2004 proceeding

Understanding Student Computational Thinking with Computational Modeling

Recently, the National Research Council's framework for next generation science standards highlighted "computational thinking" as one of its "fundamental practices". 9th Grade students taking a physics course that employed the Modeling Instruction curriculum were taught to construct computational models of physical systems. Student computational thinking was assessed using a proctored programming assignment, written essay, and a series of think-aloud interviews, where the students produced and discussed a computational model of a baseball in motion via a high-level programming environment (VPython). Roughly a third of the students in the study were successful in completing the programming assignment. Student success on this assessment was tied to how students synthesized their knowledge of physics and computation. On the essay and interview assessments, students displayed unique views of the relationship between force and motion; those who spoke of this relationship in causal (rather than observational) terms tended to have more success in the programming exercise.Comment: preprint to submit to PERC proceedings 201