Simulated single molecule microscopy with SMeagol

SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation, and optimization of advanced analysis methods for live cell single molecule microscopy data. Availability and Implementation: SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction-diffusion simulations. Documentation, source code, and binaries for recent versions of Mac OS, Windows, and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net.Comment: v2: 14 pages including supplementary text. Pre-copyedited, author-produced version of an application note published in Bioinformatics following peer review. The version of record, and additional supplementary material is available online at: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw10

A simulation study on the interactive effects of radiation and plant density on growth of cut chrysanthemum

In the present study, we used a photosynthesis-driven crop growth model to determine acceptable plant densities for cut chrysanthemum throughout the year at different intensities of supplementary light. Dry matter partitioning between leaves, stems, and flowers was simulated as a function of crop developmental stage. Leaf area index was simulated as leaf dry mass multiplied by specific leaf area, the latter being a function of season. Climatic data (hourly global radiation, greenhouse temperature, and CO2 concentration) and initial organ dry mass were model inputs. Assimilation lights were switched on and off based on time and ambient global radiation intensity. Simulated plant fresh mass with supplementary light (49 µmol m-2 s-1) for 52 cultivations (weekly plantings, reference plant densities, and length of the long and short day period) was used as reference plant fresh mass. For four other supplementary light intensities (31, 67, 85, and 104 µmol m-2 s-1), dry matter production was simulated with the reference plant density and length of the long and short day period for each planting week and plant fresh mass was calculated. The acceptable plant density was then calculated as the ratio between plant fresh mass and reference plant fresh mass multiplied by the reference density. Under low natural light intensities, plant density could be increased substantially (>30%) at increased supplementary light intensities, while maintaining the desired plant mass. Simulated light use efficiency (g additional dry mass ¿ MJ-1 additional supplementary light) was higher in winter (4.7) than in summer (3.5), whereas it hardly differed between the supplementary light intensities. This type of simulations can be used to support decisions on the acceptable level of plant density at different intensities of supplementary lighting or lighting strategies and on optimum supplementary light intensities

An automated workflow for parallel processing of large multiview SPIM recordings

Multiview light sheet fluorescence microscopy (LSFM) allows to image developing organisms in 3D at unprecedented temporal resolution over long periods of time. The resulting massive amounts of raw image data requires extensive processing interactively via dedicated graphical user interface (GUI) applications. The consecutive processing steps can be easily automated and the individual time points can be processed independently, which lends itself to trivial parallelization on a high performance cluster (HPC). Here we introduce an automated workflow for processing large multiview, multi-channel, multi-illumination time-lapse LSFM data on a single workstation or in parallel on a HPC. The pipeline relies on snakemake to resolve dependencies among consecutive processing steps and can be easily adapted to any cluster environment for processing LSFM data in a fraction of the time required to collect it.Comment: 13 pages with supplement, LATEX; 1 table, 1 figure, 2 supplementary figures, 2 supplementary lists, 2 supplementary tables; corrected error in results table, results unchange

TFBSTools: an R/bioconductor package for transcription factor binding site analysis.

Summary: The ability to efficiently investigate transcription factor binding sites (TFBSs) genome-wide is central to computational studies of gene regulation. TFBSTools is an R/Bioconductor package for the analysis and manipulation of TFBSs and their associated transcription factor profile matrices. TFBStools provides a toolkit for handling TFBS profile matrices, scanning sequences and alignments including whole genomes, and querying the JASPAR database. The functionality of the package can be easily extended to include advanced statistical analysis, data visualization and data integration. Availability and implementation: The package is implemented in R and available under GPL-2 license from the Bioconductor website (http://bioconductor.org/packages/TFBSTools/). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

INTEGRATE-Neo: A pipeline for personalized gene fusion neoantigen discovery

Abstract Motivation While high-throughput sequencing (HTS) has been used successfully to discover tumor-specific mutant peptides (neoantigens) from somatic missense mutations, the field currently lacks a method for identifying which gene fusions may generate neoantigens. Results We demonstrate the application of our gene fusion neoantigen discovery pipeline, called INTEGRATE-Neo, by identifying gene fusions in prostate cancers that may produce neoantigens. Availability and Implementation INTEGRATE-Neo is implemented in C ++ and Python. Full source code and installation instructions are freely available from https://github.com/ChrisMaherLab/INTEGRATE-Neo. Supplementary information Supplementary data are available at Bioinformatics online. </jats:sec

The influence of supplementary health insurance on switching behaviour : evidence on Swiss data

This paper focuses on the switching behaviour of sickness fund enrollees in the Swiss health insurance system. Even though the new Federal Law on Social Health Insurance (LAMal) was implemented in 1996 to promote competition among health insurers, there still remains large premium variations within cantons. This indicates that competition has not been able so far to lead to a single price, and reveals some inertia among consumers who seem reluctant to switch to less expensive funds. We investigate one possible barrier to switching behaviour, namely the influence of the supplementary insurance on the choice for basic insurance plan in Switzerland, which has not been studied so far. Our aim is to analyse the two decisions (choice of health plan, subscription to supplementary insurance contracts). We use the data of the OFAS survey conducted in 2000 on health plan choice and import some additional data on the sickness funds (number of enrollees, premiums). The decision to switch is estimated by both logit and a fixed-effects logit models; two main explanatory variables are studied: premiums (for basic insurance contracts) and supplementary insurance. The results suggest that holding a supplementary insurance contract substantially decreases the propensity to switch. The switching decision is positively influenced by the expected gain of switching, measured by the premium differential. The expected gain of switching is higher for switchers with no supplementary insurance (CHF 19.44) than for switchers with supplementary insurance (CHF 13.06). The income level has a direct positive influence on the propensity to buy a supplementary insurance. This finding suggests that the purchase of supplementary insurance is influenced, not only by risk aversion, but also by the willingness to pay for the goods covered by the supplementary insurance, which would be higher for rich people. Bad health has a negative influence on the subscription to a supplementary contract, but is no longer significant when the income is introduced into the specification. All the information about health is captured by the income level, a low income being strongly correlated with a bad health status. Income and a supplementary insurance contract are observable by the insurance company, and can be used as tools for selection.Health Insurance, Private Sector

GenePath: a System for Automated Construction of Genetic Networks from Mutant Data

Motivation: Genetic pathways are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered. Results: We have developed GenePath, an intelligent assistant that mimics expert geneticists in the analysis of genetic data. GenePath employs expert-defined patterns to uncover gene relations from the data, and uses these relations as constraints that guide the search for a plausible genetic network. GenePath provides formalism to genetic data analysis, facilitates the consideration of all the available data in a consistent and systematic manner, and aids in the examination of the large number of possible consequences of a planned experiment. It also provides an explanation mechanism that traces back every finding to the pertinent data. GenePath was successfully tested on several genetic problems. Availability: GenePath can be accessed at http://genepath.org. Supplementary information: Supplementary material is available at http://genepath.org/bi-supp