117 research outputs found
IJEMS: Iowa Joint Experiment in Microgravity Solidification
The Iowa Joint Experiment in Microgravity Solidification (IJEMS) is a cooperative effort between Iowa State University and the University of Iowa to study the formation of metal-matrix composites in a microgravity environment. Of particular interest is the interaction between the solid/liquid interface and the particles in suspension. The experiment is scheduled to fly on STS-69, Space Shuttle Endeavor on August 3, 1995. This project is unique in its heavy student participation and cooperation between the universities involved
GenomeVIP: A cloud platform for genomic variant discovery and interpretation
Identifying genomic variants is a fundamental first step toward the understanding of the role of inherited and acquired variation in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional “download and analyze” paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole-genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been used for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available data sets.</jats:p
Influence of solvent granularity on the effective interaction between charged colloidal suspensions
We study the effect of solvent granularity on the effective force between two
charged colloidal particles by computer simulations of the primitive model of
strongly asymmetric electrolytes with an explicitly added hard sphere solvent.
Apart from molecular oscillating forces for nearly touching colloids which
arise from solvent and counterion layering, the counterions are attracted
towards the colloidal surfaces by solvent depletion providing a simple
statistical description of hydration. This, in turn, has an important influence
on the effective forces for larger distances which are considerably reduced as
compared to the prediction based on the primitive model. When these forces are
repulsive, the long-distance behaviour can be described by an effective Yukawa
pair potential with a solvent-renormalized charge. As a function of colloidal
volume fraction and added salt concentration, this solvent-renormalized charge
behaves qualitatively similar to that obtained via the Poisson-Boltzmann cell
model but there are quantitative differences. For divalent counterions and
nano-sized colloids, on the other hand, the hydration may lead to overscreened
colloids with mutual attraction while the primitive model yields repulsive
forces. All these new effects can be accounted for through a solvent-averaged
primitive model (SPM) which is obtained from the full model by integrating out
the solvent degrees of freedom. The SPM was used to access larger colloidal
particles without simulating the solvent explicitly.Comment: 14 pages, 16 craphic
Effective interaction between helical bio-molecules
The effective interaction between two parallel strands of helical
bio-molecules, such as deoxyribose nucleic acids (DNA), is calculated using
computer simulations of the "primitive" model of electrolytes. In particular we
study a simple model for B-DNA incorporating explicitly its charge pattern as a
double-helix structure. The effective force and the effective torque exerted
onto the molecules depend on the central distance and on the relative
orientation. The contributions of nonlinear screening by monovalent counterions
to these forces and torques are analyzed and calculated for different salt
concentrations. As a result, we find that the sign of the force depends
sensitively on the relative orientation. For intermolecular distances smaller
than it can be both attractive and repulsive. Furthermore we report a
nonmonotonic behaviour of the effective force for increasing salt
concentration. Both features cannot be described within linear screening
theories. For large distances, on the other hand, the results agree with linear
screening theories provided the charge of the bio-molecules is suitably
renormalized.Comment: 18 pages, 18 figures included in text, 100 bibliog
Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment
Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors
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Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment.
Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs\u27 recapitulation of human tumors
Effect of cholesterol on the dipole potential of lipid membranes
The membrane dipole potential, ψd, is an electrical potential difference with a value typically in the range 150 – 350 mV (positive in the membrane interior) which is located in the lipid headgroup region of the membrane, between the linkage of the hydrocarbon chains to the phospholipid glycerol backbone and the adjacent aqueous solution. At its physiological level in animal plasma membranes (up to 50 mol%), cholesterol makes a significant contribution to ψd of approximately 65 mV; the rest arising from other lipid components of the membrane, in particular phospholipids. Via its effect on ψd, cholesterol may modulate the activity of membrane proteins. This could occur through preferential stabilization of protein conformational states. Based on its effect on ψd, cholesterol would be expected to favour protein conformations associated with a small local hydrophobic membrane thickness. Via its membrane condensing effect, which also produces an increase in ψd, cholesterol could further modulate interactions of polybasic cytoplasmic extensions of membrane proteins, in particular P-type ATPases, with anionic lipid headgroups on the membrane surface, thus leading to enhanced conformational stabilization effects and changes to ion pumping activity.Australian Research Counci
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
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