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This compressed file contains the scripts used to generate the main output tables in the article 'A trans locus causes a ribosomopathy in hypertrophic hearts that affects mRNA translation in a protein length-dependent fashion' by Franziska Witte, Jorge Ruiz-Orera et al., provisionally accepted for publication in Genome Biology (2021). These scripts can be used to map RNA-seq and Ribo-seq datasets, and use these mapped files to predict QTLs and estimate heritability, as well as to call different categories of translated ORFs. With the generated output, we generated all Figures and Results. For the rest of methods, the used public software and parameters are described in the Methods section. Code can be also accessed from: https://github.com/jorruior/witte_et_al_2021

This is an artefact for the paper "Boolean Network Sketches: A Unifying Framework for Logical Model Inference". It contains the repository with source code, benchmark models and data, as well as instructions on how to reproduce the experiments presented in the paper. For further instructions, follow the README.md file attached as part of the repository.

This code was used to produce the results in Annen and Burgisser (10.1016/j.lithos.2020.105799). The updated version Heat2D_Vol2 was used to produce results in Annen et al. 2023 Code Matlab that simulates the growth and solidification of a magma body and compute temperatures, melt fractions, dissolved and exsolved volatiles.

This submission contains the code and data used for the frequentist part of statistical analysis in paper "Meta-analysis of genotype-phenotype associations in Bardet-Biedl Syndrome uncovers differences among causative genes". The data can also be accessed and explored in an intractive web interface at http://bardet-biedl.img.cas.cz.

Source code for the experiments in the paper: Chance-constrained optimization formulation for conceptual ship design: A comparison of metaheuristic algorithms

The archive of the tool Symbiotic 8 that was used in the SV-COMP 2021 competition. Symbiotic 8 extends the traditional combination of static analyses, instrumentation, program slicing, and symbolic execution with one substantial novelty, namely a technique mixing symbolic execution with k-induction. This technique can prove the correctness of programs with possibly unbounded loops, which cannot be done by classic symbolic execution. Symbiotic 8 delivers also several other improvements. In particular, we have modified our fork of the symbolic executor Klee to support the comparison of symbolic pointers. Further, we have tuned the shape analysis tool Predator (integrated already in Symbiotic 7) to perform better on LLVM bitcode. We have also developed a light-weight analysis of relations between variables that can prove the absence of out-of-bound accesses to arrays. The tool can be found also on the official site of the competition: https://gitlab.com/sosy-lab/sv-comp/archives-2021/-/blob/master/2021/symbiotic.zip, and also on the release pages of Symbiotic where we publish also versions after bugfixes: https://github.com/staticafi/symbiotic/releases

The software tool is developed on demand of Radiological Department of Faculty Hospital of Královské Vinohrady, with the aim to provide a tool to estimate the percentage of pneumonia (or COVID-19 presence) in lungs. Paper Estimation of Covid-19 lungs damage based on computer tomography images analysis presenting the tool is available on F1000reserach DOI: 10.12688/f1000research.109020.1. The underlying dataset is published in Zenodo (DOI:10.5281/zenodo.5805939). One of the challenges was to design a tool that would be available without complicated install procedures and would process data in a reasonable time even on office computers. For this reason, 8-bit and 16-bit version of the tool exists. The FIJI software (or ImageJ with Bio-Formats plugin installed) was selected as the best candidate. Examples of use and tutorials are available at GitHub. Underlying data: DOI:10.5281/zenodo.5805939 The first five datasets are analyzed using this tool, with results and parameters to repeat the analysis in results_csv.csv or results.xlsx. Contributions: Martin SCHÄTZ: Coding, tool testing, data curation, data set analysis Olga RUBEŠOVÁ: Code review, tutorial preparation, tool testing, data set analysis Jan MAREŠ: Tool testing, data set analysis Alan SPARK: Tool testing The work was funded by the Ministry of Education, Youth and Sports by grant ‘Development of Advanced Computational Algorithms for evaluating post-surgery rehabilitation’ number LTAIN19007. The work was also supported from the grant of Specific university research – grant No FCHI 2022-001.

What's Changed Update README.md by @adujovic in https://github.com/Mellechowicz/JorG/pull/5 Correct version of counting interactions in the Ising model solver��� by @adujovic in https://github.com/Mellechowicz/JorG/pull/6 v0.2.1 by @adujovic in https://github.com/Mellechowicz/JorG/pull/7 New Contributors @adujovic made their first contribution in https://github.com/Mellechowicz/JorG/pull/5 Full Changelog: https://github.com/Mellechowicz/JorG/compare/v0.1.2...v0.3.0

What's Changed BIDS App preparation and serial/parallel behavior by @ericearl in https://github.com/nimh-dsst/dsst-defacing-pipeline/pull/21 Integrate into bids tree by @Arshitha in https://github.com/nimh-dsst/dsst-defacing-pipeline/pull/30 integrating generate renders to pipeline by @Arshitha in https://github.com/nimh-dsst/dsst-defacing-pipeline/pull/32 Full Changelog: https://github.com/nimh-dsst/dsst-defacing-pipeline/compare/v1.0.0...v1.0.1