{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "chem-bla-ics",
  "description": "Chemblaics (pronounced chem-bla-ics) is the science that uses open science and computers to solve problems in chemistry, biochemistry and related fields.",
  "home_page_url": "https://chem-bla-ics.linkedchemistry.info/",
  "feed_url": "https://chem-bla-ics.linkedchemistry.info/2024/03/17/two-papers.json",
  "icon": "https://chem-bla-ics.linkedchemistry.info/assets/images/chem-bla-ics_logo.png",
  "language": "en",
  "authors": [
    {
      "name": "Egon Willighagen",
      "url": "https://orcid.org/0000-0001-7542-0286",
      "_orcid": "0000-0001-7542-0286"
    }
  ],
  "items": [

    {
      "id": "https://doi.org/10.59350/zds99-03s42",
      "url": "https://chem-bla-ics.linkedchemistry.info/2024/03/17/two-papers.html",
      "title": "Reusing data: two new papers",
      "content_html": "<p>My research is about the interaction of (machine) representation and the impact on the success of\ndata analysis (matchine learning, chemometrics, AI, etc). See the posts\n<a href=\"https://chem-bla-ics.linkedchemistry.info/2010/08/09/molecular-chemometrics-principles-1.html\">about</a>\n<a href=\"https://chem-bla-ics.linkedchemistry.info/2010/08/12/molecular-chemometrics-principles-2-be.html\">molecular</a>\n<a href=\"https://chem-bla-ics.linkedchemistry.info/2010/08/14/molecular-chemometrics-principles-3.html\">chemometrics</a>.\nThis got me into <a href=\"https://chem-bla-ics.linkedchemistry.info/tag/fair\">FAIR</a>: making data interoperable\nand being able to (really) reuse data is the starting point of doing research.</p>\n\n<p>So, when I get the chance to see something where I worked on to make more FAIR actually being used,\nI love to push the boundaries of FAIR a bit extra. The study of representation of molecules and molecular\nsystems is not quite a popular science, but I find it important. Two new papers got recently published\nto which I contributed from this perspective.</p>\n\n<p>The first paper by Anna Niarakis <i>et al.</i> is about using the SARS-CoV-2/COVID-19 knowledge base we\nhave collected of the past 4 years (doi:<a href=\"https://doi.org/10.3389/fimmu.2023.1282859\">10.3389/fimmu.2023.1282859</a>).\nFor me, this started with a WikiPathways with early knowledge about the virus proteins. I think\nin this and earlier papers, we improved our open science and bioinformatics and are actually\nmore ready for a next pandemic, which inevitably will come.</p>\n\n<p>The second paper by Alfaro Serrano <i>et al.</i> is about how access to data remains key to many\nthings, and this, obviously, includes the Sustainable Development Goals (SDGs)\n(doi:<a href=\"https://doi.org/10.1039/D3SU00148B\">10.1039/D3SU00148B</a>). When it comes down\nto the face/off of FAIR versus Open, I think Open has more impact, hands-down.</p>\n\n<p>About the latter, I recently wrote up ten simple actions you can take to make your\nnanosafety research output more FAIR (doi:<a href=\"https://doi.org/10.5281/zenodo.10533126\">10.5281/zenodo.10533126</a>).</p>\n\n<h4>References</h4>\n<div class=\"csl-bib-body\">\n    <div class=\"csl-entry\">Niarakis, A., Ostaszewski, M., Mazein, A., Kuperstein, I., Kutmon, M., Gillespie, M. E., Funahashi, A., Acencio, M. L., Hemedan, A., Aichem, M., Klein, K., Czauderna, T., Burtscher, F., Yamada, T. G., Hiki, Y., Hiroi, N. F., Hu, F., Pham, N., Ehrhart, F., … Schneider, R. (2024). Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. <i>Frontiers in Immunology</i>, <i>14</i>. https://doi.org/10.3389/fimmu.2023.1282859 <a href=\"https://doi.org/10.3389/FIMMU.2023.1282859\">CrossRef</a> <a href=\"https://qlever.scholia.wiki/doi/10.3389/FIMMU.2023.1282859\">Scholia</a></div>\n    <div class=\"csl-entry\">Serrano, B. A., Gheorghe, L. C., Exner, T. E., Resch, S., Wolf, C., Himly, M., Falk, A., Bossa, N., Vazquez, S., Papadiamantis, A. G., Afantitis, A., Melagraki, G., Maier, D., Saramveis, H., Willighagen, E., Lobaskin, V., Oldfield, J. D., &#38; Lynch, I. (2024). The role of FAIR nanosafety data and nanoinformatics in achieving the UN sustainable development goals: the NanoCommons experience. <i>RSC Sustainability</i>, <i>2</i>(5), 1378–1399. https://doi.org/10.1039/d3su00148b <a href=\"https://doi.org/10.1039/D3SU00148B\">CrossRef</a> <a href=\"https://qlever.scholia.wiki/doi/10.1039/D3SU00148B\">Scholia</a></div>\n    <div class=\"csl-entry\">Willighagen, E. (2024). Ten simple actions to make NanoSafety Cluster Research Output more Findable. <i>Zenodo</i>. https://doi.org/10.5281/ZENODO.10533126 <a href=\"https://doi.org/10.5281/ZENODO.10533126\">CrossRef</a> <a href=\"https://qlever.scholia.wiki/doi/10.5281/ZENODO.10533126\">Scholia</a></div>\n  </div>",
      "summary": "My research is about the interaction of (machine) representation and the impact on the success of data analysis (matchine learning, chemometrics, AI, etc). See the posts about molecular chemometrics. This got me into FAIR: making data interoperable and being able to (really) reuse data is the starting point of doing research.",
      
      "date_published": "2024-03-17T00:00:00+00:00",
      "date_modified": "2024-03-17T00:00:00+00:00",
      "tags": ["covid19","fair","nanosafety","nanocommons"],
      "_references": [
        
          
          
            { "url": "https://doi.org/10.3389/FIMMU.2023.1282859", "doi": "10.3389/FIMMU.2023.1282859"
             }
            ,
          
        
          
          
            { "url": "https://doi.org/10.1039/D3SU00148B", "doi": "10.1039/D3SU00148B"
             }
            ,
          
        
          
          
            { "url": "https://doi.org/10.5281/ZENODO.10533126", "doi": "10.5281/ZENODO.10533126"
             }
            
          
        ],
      
      
      
      
      
      
        "authors": [ { "name": "Egon Willighagen", "url": "https://orcid.org/0000-0001-7542-0286" } ]
      
    }

  ]
}