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  • Machine learning a model for RNA structure prediction

    Authors: Nicola Calonaci, Alisha Jones, Francesca Cuturello, Michael Sattler, Giovanni Bussi
    DOI: 10.1093/nargab/lqaa090
    Submitted by giovannibussi      

    Why should we attempt to reproduce this paper?

    The method is trained on the data that were available, but it is meant to be re-trainable as soon as new data are published. It would be great to be really sure that even someone else will be able to do it. In case we receive any feedback, we would be really happy to improve our Github repository so as to make the reproduction easier!

  • REMoDNaV: robust eye-movement classification for dynamic stimulation

    Authors: Asim H. Dar, Adina S. Wagner, Michael Hanke
    DOI: https://doi.org/10.3758/s13428-020-01428-x
    Submitted by adswa    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   3
    Why should we attempt to reproduce this paper?

    In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at https://github.com/psychoinformatics-de/paper-remodnav). We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.

  • Where should new parkrun events be located? Modelling the potential impact of 200 new events on socio-economic inequalities in access and participation

    Authors: Schneider PP, Smith RA, Bullas AM, Bayley T, Haake SS, Brennan A, Goyder E
    Submitted by hub-admin    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   3
    Why should we attempt to reproduce this paper?

    If all went right, the analysis should be fully reproducible without the need to make any adjustments. The paper aims to find optimal locations for new parkruns, but we were not 100% sure how 'optimal' should be defined. We provide a few examples, but the code was meant to be flexible enough to allow potential decision makers to specify their own, alternative objectives. The spatial data set is also quite interesting and fun to play around with. Cave: The full analysis takes a while to run (~30+ min) and might require >= 8gb ram.

  • Spatial modelling of rice yield losses in Tanzania due to bacterial leaf blight and leaf blast in a changing climate

    Authors: C. Duku, A. H. Sparks, S. J. Zwart.
    DOI: 10.1007/s10584-015-1580-2
    Submitted by hub-admin    
      Mean reproducibility score:   4.0/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    This was my third attempt at making a paper fully reproducible. To date I it's the most reproducible that I have published. I'm interested to know what stumbling blocks exist that I'm not aware of (aside from needing software like ArcGIS to fully rerun the complete analysis).

    Tags: Python R ArcGIS

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