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  • Authors: Pervouchine, Dmitri; Pervouchine, Dmitri;

    The integrative pipeline for splicing analyses: 1) Quantifies splice junctions and splice boundaries; 2) Calculates splicing indices, exon- and intron-centric; 3) Analyzes micro-exons and local splice-graph structure.

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  • Authors: Jones, Kate E.; Aodha, Oisin Mac;

    Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. This tool helps better assess bat population trends accurately and allow the detection and classification of bat calls in large collections of audio recordings.

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    Authors: Menden, Kevin; Kast, Tristan; Hörtenhuber, Matthias; Ewels, Philip A.; +2 Authors

    nf-core/cageseq is a bioinformatics analysis pipeline used for CAGE-seq sequencing data.

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    bio.tools
    Software . 2021
    License: MIT
    Data sources: bio.tools
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ bio.toolsarrow_drop_down
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      bio.tools
      Software . 2021
      License: MIT
      Data sources: bio.tools
  • Authors: Kreysing, Moritz;

    Multiplexed wave-optical simulations of light-sheet microscopy.

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  • Authors: Rudolph, Max Gustav; Wöhling, Thomas; Wagener, Thorsten; Hartmann, Andreas;

    This repository contains Python code and data to reproduce results and figures from the journal article "Extending GLUE with Multilevel Methods to Accelerate Statistical Inversion of Hydrological Models". Consider the readme.txt for further information and steps on how to reproduce results. To be able to reproduce the results, make sure you have Anaconda installed on your machine. The results were originally generated on machines with Windows x64 operating systems and Intel CPUs.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Terrucha, Inês; Fernandez Domingos, Elias;
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    ZENODO
    Software . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Software . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Software . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Software . 2023
      License: CC BY
      Data sources: Datacite
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  • Authors: Fernandez, Luciano; Fernandez, Luciano;

    Tool developed to automate visualization, analysis and exploration of complex and highly resolved microbial growth data, as well as standardized extraction of the fitness components it contains. It is hope that this tool will promote simplicity, transparency and standardization in microbial growth phenomics, and provide a portal with the standalone software and online tools so that other microbiology labs can easily upload, assess and visualize their growth data.

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    Authors: Jonathan Harrison;

    Implementation of a minimal computational model of HURP dynamics on kinetochore-fibres and inference methods to fit this model to experimental data via Markov chain Monte Carlo.

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    ZENODO
    Software . 2022
    Data sources: Datacite
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    ZENODO
    Software . 2022
    Data sources: ZENODO
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      ZENODO
      Software . 2022
      Data sources: Datacite
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      ZENODO
      Software . 2022
      Data sources: ZENODO
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    This repository contains two scripts to analyse drone Digital Elevation Models (DEMs) against RTK GPS Ground Control Points. The script was prepared to illustrate the results of Casella et al. (under review), that compare the performance of different drone flight altitudes and different cameras. The two required inputs are: an Excel file containing Ground Control Points (used in Agisoft Photoscan or similar software to georeference the DEM) and Control Points (indipendent RTK GPS points used as control). The excel file needs to be formatted as in the example. a folder containing the DEMs (geotiff format) derived from each drone flight. The file name will serve as label for each figure. Drone_data_extract.m - This script compares Control Points and DEM elevations, and produces a figure showing the result of the comparison for each DEM in the dataset. The script also writes the results of the DEM analysis as text, comma separated files. This script needs the Matlab 'Mapping Toolbox', 'Image Processing Toolbox' and 'Statistics and Machine Learning Toolbox' Data_analysis.m - This script takes the results of the previous step and plots them together into a summary figure. Before the final figure is produced, the user needs to insert manually the picture overlap, that is usually available in the processing reports of photogrammetric software. This script needs the Matlab 'Statistics and Machine Learning Toolbox' Version 1.0 Version released upon acceptance of the related MS. Version 1.1 Update of Ver.1.0. Added all Digital Elevation Models and Agisoft Photoscan reports. No modifications to the code.

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    ZENODO
    Software . 2019
    Data sources: Datacite
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    ZENODO
    Software . 2019
    Data sources: ZENODO
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    ZENODO
    Software . 2019
    Data sources: ZENODO
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      ZENODO
      Software . 2019
      Data sources: Datacite
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      ZENODO
      Software . 2019
      Data sources: ZENODO
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      ZENODO
      Software . 2019
      Data sources: ZENODO
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    Authors: Lenaerts, Tom;

    This software was used to generate the data and figures shown in the paper "Evolution of Theory of Mind" by Tom Lenaerts, Marco Saponara, Jorge M. Pacheco and Francisco C. Santos

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    ZENODO
    Software . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Software . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Software . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Software . 2023
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      Data sources: Datacite
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  • Authors: Palumbo, Emilio; Palumbo, Emilio;

    GRAPE 2.0 provides an extensive pipeline for RNA-Seq analyses. It allows the creation of an automated and integrated workflow to manage, analyse and visualize RNA-Seq data.

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    bio.tools
    Software . 2016
    License: GPL-3.0
    Data sources: bio.tools
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      bio.tools
      Software . 2016
      License: GPL-3.0
      Data sources: bio.tools
  • Authors: Ribeca, Paolo; Ribeca, Paolo;

    A set of very optimized tools for indexing/querying huge genomes/files. Provided so far: a very fast exact mapper, and an unconstrained split-mapper

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    bio.tools
    Software . 2016
    License: GPL-3.0
    Data sources: bio.tools
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      bio.tools
      Software . 2016
      License: GPL-3.0
      Data sources: bio.tools
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    Authors: Lenaerts, Tom;

    Digenic Diseases Database (DiDA) provides detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance.

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    bio.tools
    Software . 2016
    License: CC-BY-NC-4.0
    Data sources: bio.tools
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      bio.tools
      Software . 2016
      License: CC-BY-NC-4.0
      Data sources: bio.tools
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    Authors: Amighi, Milan; Roshandel, Nima; Menet, Sebastien; Shhaitly, Mariane; +2 Authors

    {"references": ["Tom M. Speed and Separation Monitoring for Robotic Applications. April 2022. Link : https://perma.cc/NQ4T-Q63R", "Paul Glogowski, Alexander Bohmer, Alfred Hypki and Bernd Kuhlenkotter. Robot Speed Adaption in Multiple Trajectory Planning and Integration in a Simulation Tool for Human-Robot Interaction. April 2021. Link : https://perma.cc/S7VM-6FH9", "Marek Vagas and Alena Galajdova. APPLICATION OF SPEED AND SEPARATION MONITORING TECHNIQUE AT AUTOMATED ASSEMBLY PROCESS. June 2021. DOI: 10.17973/MMSJ.2021_6_2021036", "Urban B. Himmelsbach, Thomas M. Wendt, Nikolai Hangst, Philipp Gawron and Lukas Stiglmeier. Human\u2013Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human\u2013Robot Collaboration. October 2021. DOI: 10.3390/s21217144", "Jeremy A. Marvel and Rick Norcross. Implementing speed and separation monitoring in collaborative robot workcells. April 2017. DOI: https://doi.org/10.1016/j.rcim.2016.08.001", "TDK. Ultra-low Power Integrated Ultrasonic Time-of-Flight Range Sensor (CH101 datasheet). Link : https://perma.cc/JV4A-EGK4", "Universal Robots. UR10e - user manual. Link: https://perma.cc/4T8B-J9SE"]} Code Purpose: The code developed allows readers to understand and learn how the speed and separation monitoring algorithm works and how the various variables affect the distances where the robot is slowing down and stopping to prevent any collision. To ease the understanding, we are using constant velocities. Quick Start Guide: Download the latest release of Matlab: https://www.mathworks.com/downloads Clone this repository to download the latest version of the script. Open the live script SSM_Simulation.mlx in matlab. Set the variables explained in the script and then run the script by pressing the green button. Also watch the video tutorial below for better understanding. Video Tutorial: https://youtu.be/4QspuZQLBRk Software: Compiled on Matlab R2022a Disclaimer: The algorithm is based on TS/ISO15066 and can be used to estimate and simulate the speed and separation monitoring behaviour. Please only use this script in research, taking extra safety measures to prevent injuries. Consult a certified integrator to implement speed and separation monitoring in a safety-critical manufacturing context. If you use this software, please cite it using the metadata from this file.

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    ZENODO
    Software . 2022
    Data sources: Datacite
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      ZENODO
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    Authors: Hernandez-Ferrer, Carles; Gonzalez, Juan R.;

    Package that allows to explore the exposome and to perform association analyses between exposures and health outcomes.

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    bio.tools
    Software . 2018
    License: MIT
    Data sources: bio.tools
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      bio.tools
      Software . 2018
      License: MIT
      Data sources: bio.tools
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    Authors: Tosatto, Silvio C. E.;

    Database of protein disorder and mobility annotations.

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    bio.tools
    Software . 2015
    License: CC-BY-4.0
    Data sources: bio.tools
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      bio.tools
      Software . 2015
      License: CC-BY-4.0
      Data sources: bio.tools
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    Authors: Patel, Harshil; Ewels, Philip A.; Garcia, Maxime U.; Espinosa-Carrasco, Jose;

    nfcore/atacseq is a bioinformatics analysis pipeline used for ATAC-seq data.

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    bio.tools
    Software . 2021
    License: MIT
    Data sources: bio.tools
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      bio.tools
      Software . 2021
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  • Authors: Vranken, Wim;

    Protein backbone dynamics prediction from sequence.

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  • Authors: Planas-Iglesias, Joan;

    This tool uses protein structural features (protein loops as classified in ArchDB and/or domains as classified in SCOP) to determine whether any pair of proteins interact or not. To do that, it uses data from both known protein interactions and putative non-interacting proteins, assigning positive and negative scores to the structural features. The main result page displays a summary of the predictions for the given protein pairs with available detailed data for each prediction.

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  • Authors: Fuentes, Magdalena; Bittner, Rachel; Plaja-Roglans, Genís; Cortès, Guillem; +10 Authors