The Nanomaterial Data Curation Initiative: A collaborative approach to assessing, evaluating, and advancing the state of the field

Scholarly Works

• Mortensen, H. M.; Beach, B.; Slaughter, W.; Senn, J.; Williams, A.; Boyes, W. Translating nanoEHS data using EPA NaKnowBase and the resource description framework. F1000Research 2024, 13, 169. doi:10.12688/f1000research.141056.1
• Amos, J. D.; Zhang, Z.; Tian, Y.; Lowry, G. V.; Wiesner, M. R.; Hendren, C. O. Knowledge and Instance Mapping: architecture for premeditated interoperability of disparate data for materials. Scientific data 2024, 11, 173. doi:10.1038/s41597-024-03006-8
• Carter, J.; Bjorkland, R.; Boyes, W. K.; Geraci, C.; Hackley, V. A.; Howard, J.; Kennedy, A.; Linkov, I.; Matheson, J.; Mortensen, H.; Muianga, C.; Petersen, E. J.; Savage, N.; Schulte, P.; Standridge, S.; Thomas, T.; Trump, B.; Nadadur, S. U. S. federal perspective on critical research issues in nanoEHS. Environmental Science: Nano 2023, 10, 2623–2633. doi:10.1039/d3en00062a
• Barrick, A.; Métais, I.; Ettajani, H.-P.; Marion, J.-M.; Châtel, A. Establishing FAIR (Findable, Accessible, Interoperable and Reusable) principles for estuarine organisms exposed to engineered nanomaterials. International Journal of Data Science and Analytics 2023, 16, 407–419. doi:10.1007/s41060-023-00447-z
• Dumit, V. I.; Ammar, A.; Bakker, M. I.; Bañares, M. A.; Bossa, C.; Costa, A.; Cowie, H.; Drobne, D.; Exner, T. E.; Farcal, L.; Friedrichs, S.; Furxhi, I.; Grafström, R.; Haase, A.; Himly, M.; Jeliazkova, N.; Lynch, I.; Maier, D.; Noorlander, C. W.; Shin, H. K.; Soler-Illia, G. J.; Suarez-Merino, B.; Willighagen, E.; Nymark, P. From principles to reality. FAIR implementation in the nanosafety community. Nano Today 2023, 51, 101923. doi:10.1016/j.nantod.2023.101923
• Furxhi, I.; Willighagen, E.; Evelo, C.; Costa, A.; Gardini, D.; Ammar, A. A data reusability assessment in the nanosafety domain based on the NSDRA framework followed by an exploratory quantitative structure activity relationships (QSAR) modeling targeting cellular viability. NanoImpact 2023, 31, 100475. doi:10.1016/j.impact.2023.100475
• Yan, X.; Yue, T.; Winkler, D. A.; Yin, Y.; Zhu, H.; Jiang, G.; Yan, B. Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation. Chemical reviews 2023, 123, 8575–8637. doi:10.1021/acs.chemrev.3c00070
• Hofer, S.; Hofstätter, N.; Punz, B.; Hasenkopf, I.; Johnson, L.; Himly, M. Immunotoxicity of nanomaterials in health and disease: Current challenges and emerging approaches for identifying immune modifiers in susceptible populations. Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology 2022, 14, e1804. doi:10.1002/wnan.1804
• Khan, B. M.; Cohen, Y. doi:10.1002/9781119817512.ch9
• Hasenkopf, I.; Mills-Goodlet, R.; Johnson, L.; Rouse, I.; Geppert, M.; Duschl, A.; Maier, D.; Lobaskin, V.; Lynch, I.; Himly, M. Computational prediction and experimental analysis of the nanoparticle-protein corona: Showcasing an in vitro-in silico workflow providing FAIR data. Nano Today 2022, 46, 101561. doi:10.1016/j.nantod.2022.101561
• Boyes, W. K.; Beach, B.; Chan, G.; Thornton, B. L. M.; Harten, P.; Mortensen, H. M. An EPA database on the effects of engineered nanomaterials-NaKnowBase. Scientific data 2022, 9, 12. doi:10.1038/s41597-021-01098-0
• Amos, J. D.; Tian, Y.; Zhang, Z.; Lowry, G.; Wiesner, M. R.; Hendren, C. O. The NanoInformatics Knowledge Commons: Capturing spatial and temporal nanomaterial transformations in diverse systems. NanoImpact 2021, 23, 100331. doi:10.1016/j.impact.2021.100331
• Yu, H.; Luo, D.; Dai, L.; Cheng, F. In silico nanosafety assessment tools and their ecosystem-level integration prospect. Nanoscale 2021, 13, 8722–8739. doi:10.1039/d1nr00115a
• Jeliazkova, N.; Apostolova, M. D.; Andreoli, C.; Barone, F.; Barrick, A.; Battistelli, C. L.; Bossa, C.; Botea-Petcu, A.; Châtel, A.; De Angelis, I.; Dusinska, M.; Yamani, N. E.; Gheorghe, D.; Giusti, A.; Gómez-Fernández, P.; Grafström, R. C.; Gromelski, M.; Jacobsen, N. R.; Jeliazkov, V.; Jensen, K. A.; Kochev, N.; Kohonen, P.; Manier, N.; Mariussen, E.; Mech, A.; Navas, J. M.; Paskaleva, V.; Precupas, A.; Puzyn, T.; Rasmussen, K.; Ritchie, P.; Llopis, I. R.; Rundén-Pran, E.; Sandu, R.; Shandilya, N.; Tanasescu, S.; Haase, A.; Nymark, P. Towards FAIR nanosafety data. Nature nanotechnology 2021, 16, 644–654. doi:10.1038/s41565-021-00911-6
• Rumble, J. On the Categorization of Nanomaterials. 2020.
• Ammar, A.; Bonaretti, S.; Winckers, L. A.; Quik, J. T.; Bakker, M.; Maier, D.; Lynch, I.; van Rijn, J.; Willighagen, E. A Semi-Automated Workflow for FAIR Maturity Indicators in the Life Sciences. Nanomaterials (Basel, Switzerland) 2020, 10, 2068. doi:10.3390/nano10102068
• Papadiamantis, A. G.; Klaessig, F.; Exner, T.; Hofer, S.; Hofstaetter, N.; Himly, M.; Williams, M. A.; Doganis, P.; Hoover, M. D.; Afantitis, A.; Melagraki, G.; Nolan, T. S.; Rumble, J.; Maier, D.; Lynch, I. Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data. Nanomaterials (Basel, Switzerland) 2020, 10, 2033. doi:10.3390/nano10102033
• David, C.; Barrow, M.; Murray, P.; Rosseinsky, M. J.; Owen, A.; Liptrott, N. J. In Vitro Determination of the Immunogenic Impact of Nanomaterials on Primary Peripheral Blood Mononuclear Cells. International journal of molecular sciences 2020, 21, 5610. doi:10.3390/ijms21165610
• Yan, X.; Sedykh, A.; Wang, W.; Yan, B.; Zhu, H. Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations. Nature communications 2020, 11, 2519. doi:10.1038/s41467-020-16413-3
• Afantitis, A.; Melagraki, G.; Isigonis, P.; Tsoumanis, A.; Varsou, D.-D.; Valsami-Jones, E.; Papadiamantis, A. G.; Ellis, L. J. A.; Sarimveis, H.; Doganis, P.; Karatzas, P.; Tsiros, P.; Liampa, I.; Lobaskin, V.; Greco, D.; Serra, A.; Kinaret, P. A. S.; Saarimäki, L. A.; Grafström, R. C.; Kohonen, P.; Nymark, P.; Willighagen, E.; Puzyn, T.; Rybińska-Fryca, A.; Lyubartsev, A. P.; Jensen, K. A.; Brandenburg, J. G.; Lofts, S.; Svendsen, C.; Harrison, S.; Maier, D.; Tämm, K.; Jänes, J.; Sikk, L.; Dusinska, M.; Longhin, E.; Rundén-Pran, E.; Mariussen, E.; Yamani, N. E.; Unger, W.; Radnik, J.; Tropsha, A.; Cohen, Y.; Leszczynski, J.; Hendren, C. O.; Wiesner, M. R.; Winkler, D. A.; Suzuki, N.; Yoon, T. H.; Choi, J.-S.; Sanabria, N.; Gulumian, M.; Lynch, I. NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment. Computational and structural biotechnology journal 2020, 18, 583–602. doi:10.1016/j.csbj.2020.02.023

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