Dive into the research topics where FASC - Chemistry is active. These topic labels come from the works of this organization's members. Together they form a unique fingerprint.


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  • CATMoS: Collaborative acute toxicity modeling suite

    Mansouri, K., Karmaus, A. L., Fitzpatrick, J., Patlewicz, G., Pradeep, P., Alberga, D., Alepee, N., Allen, T. E. H., Allen, D., Alves, V. M., Andrade, C. H., Auernhammer, T. R., Ballabio, D., Bell, S., Benfenati, E., Bhattacharya, S., Bastos, J. V., Boyd, S., Brown, J. B., Capuzzi, S. J. & 82 others, Chushak, Y., Ciallella, H., Clark, A. M., Consonni, V., Daga, P. R., Ekins, S., Farag, S., Fedorov, M., Fourches, D., Gadaleta, D., Gao, F., Gearhart, J. M., Goh, G., Goodman, J. M., Grisoni, F., Grulke, C. M., Hartung, T., Hirn, M., Karpov, P., Korotcov, A., Lavado, G. J., Lawless, M., Li, X., Luechtefeld, T., Lunghini, F., Mangiatordi, G. F., Marcou, G., Marsh, D., Martin, T., Mauri, A., Muratov, E. N., Myatt, G. J., Nguyen, D. T., Nicolotti, O., Note, R., Pande, P., Parks, A. K., Peryea, T., Polash, A. H., Rallo, R., Roncaglioni, A., Rowlands, C., Ruiz, P., Russo, D. P., Sayed, A., Sayre, R., Sheils, T., Siegel, C., Silva, A. C., Simeonov, A., Sosnin, S., Southall, N., Strickland, J., Tang, Y., Teppen, B., Tetko, I. V., Thomas, D., Tkachenko, V., Todeschini, R., Toma, C., Tripodi, I., Trisciuzzi, D., Tropsha, A., Varnek, A., Vukovic, K., Wang, Z., Wang, L., Waters, K. M., Wedlake, A. J., Wijeyesakere, S. J., Wilson, D., Xiao, Z., Yang, H., Zahoranszky-Kohalmi, G., Zakharov, A. V., Zhang, F. F., Zhang, Z., Zhao, T., Zhu, H., Zorn, K. M., Casey, W. & Kleinstreuer, N. C., 2021, In: Environmental health perspectives. 129, 4, 047013.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids

    Jia, X., Ciallella, H. L., Russo, D. P., Zhao, L., James, M. H. & Zhu, H., Mar 15 2021, In: ACS Sustainable Chemistry and Engineering. 9, 10, p. 3909-3919 11 p.

    Research output: Contribution to journalArticlepeer-review

    1 Scopus citations
  • Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches

    Ciallella, H. L., Russo, D. P., Aleksunes, L. M., Grimm, F. A. & Zhu, H., Apr 2021, In: Laboratory Investigation. 101, 4, p. 490-502 13 p.

    Research output: Contribution to journalArticlepeer-review

    3 Scopus citations