Sfoglia per Autore
Predicting molecular activity on nuclear receptors with deep and machine learning
2021 Valsecchi, C; Grisoni, F; Consonni, V; Ballabio, D; Todeschini, R
CATMoS: Collaborative Acute Toxicity Modeling Suite
2021 Mansouri, K; Karmaus, A; Fitzpatrick, J; Patlewicz, G; Pradeep, P; Alberga, D; Alepee, N; Allen, T; Allen, D; Alves, V; Andrade, C; Auernhammer, T; Ballabio, D; Bell, S; Benfenati, E; Bhattacharya, S; Bastos, J; Boyd, S; Brown, J; Capuzzi, S; Chushak, Y; Ciallella, H; Clark, A; Consonni, V; Daga, P; Ekins, S; Farag, S; Fedorov, M; Fourches, D; Gadaleta, D; Gao, F; Gearhart, J; Goh, G; Goodman, J; Grisoni, F; Grulke, C; Hartung, T; Hirn, M; Karpov, P; Korotcov, A; Lavado, G; Lawless, M; Li, X; Luechtefeld, T; Lunghini, F; Mangiatordi, G; Marcou, G; Marsh, D; Martin, T; Mauri, A; Muratov, E; Myatt, G; Nguyen, D; Nicolotti, O; Note, R; Pande, P; Parks, A; Peryea, T; Polash, A; Rallo, R; Roncaglioni, A; Rowlands, C; Ruiz, P; Russo, D; Sayed, A; Sayre, R; Sheils, T; Siegel, C; Silva, A; Simeonov, A; Sosnin, S; Southall, N; Strickland, J; Tang, Y; Teppen, B; Tetko, I; Thomas, D; Tkachenko, V; Todeschini, R; Toma, C; Tripodi, I; Trisciuzzi, D; Tropsha, A; Varnek, A; Vukovic, K; Wang, Z; Wang, L; Waters, K; Wedlake, A; Wijeyesakere, S; Wilson, D; Xiao, Z; Yang, H; Zahoranszky-Kohalmi, G; Zakharov, A; Zhang, F; Zhang, Z; Zhao, T; Zhu, H; Zorn, K; Casey, W; Kleinstreuer, N
Geographical identification of Chianti red wine based on ICP-MS element composition
2020 Bronzi, B; Brilli, C; Beone, G; Fontanella, M; Ballabio, D; Todeschini, R; Consonni, V; Grisoni, F; Parri, F; Buscema, M
Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study
2020 Valsecchi, C; Grisoni, F; Consonni, V; Ballabio, D
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
2020 Mansouri, K; Kleinstreuer, N; Abdelaziz, A; Alberga, D; Alves, V; Andersson, P; Andrade, C; Bai, F; Balabin, I; Ballabio, D; Benfenati, E; Bhhatarai, B; Boyer, S; Chen, J; Consonni, V; Farag, S; Fourches, D; García-Sosa, A; Gramatica, P; Grisoni, F; Grulke, C; Hong, H; Horvath, D; Hu, X; Huang, R; Jeliazkova, N; Li, J; Li, X; Liu, H; Manganelli, S; Mangiatordi, G; Maran, U; Marcou, G; Martin, T; Muratov, E; Nguyen, D; Nicolotti, O; Nikolov, N; Norinder, U; Papa, E; Petitjean, M; Piir, G; Pogodin, P; Poroikov, V; Qiao, X; Richard, A; Roncaglioni, A; Ruiz, P; Rupakheti, C; Sakkiah, S; Sangion, A; Schramm, K; Selvaraj, C; Shah, I; Sild, S; Sun, L; Taboureau, O; Tang, Y; Tetko, I; Todeschini, R; Tong, W; Trisciuzzi, D; Tropsha, A; Van Den Driessche, G; Varnek, A; Wang, Z; Wedebye, E; Williams, A; Xie, H; Zakharov, A; Zheng, Z; Judson, R
Deep Ranking Analysis by Kendall Eigenvectors (DRAKE): A Wizard for Ranking and Multi-Criteria Decision Making
2019 Todeschini, R; Grisoni, F; Ballabio, D
Consensus Prediction of Androgen Receptor Activity within the CoMPARA Project
2019 Ballabio, D; Valsecchi, C; Grisoni, F; Consonni, V; Mansouri, K; Todeschini, R
Integrated QSAR Models to Predict Acute Oral Systemic Toxicity
2019 Ballabio, D; Grisoni, F; Consonni, V; Todeschini, R
Acceptable-by-design QSARs to predict the dietary biomagnification of organic chemicals in fish
2019 Grisoni, F; Consonni, V; Vighi, M
Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project
2019 Grisoni, F; Consonni, V; Ballabio, D
Deep Ranking Analysis by Power Eigenvectors (DRAPE): A wizard for ranking and multi-criteria decision making
2019 Todeschini, R; Grisoni, F; Ballabio, D
Structural alerts for the identification of bioaccumulative compounds
2019 Valsecchi, C; Grisoni, F; Consonni, V; Ballabio, D
On the Misleading Use of QF32 for QSAR Model Comparison
2019 Consonni, V; Todeschini, R; Ballabio, D; Grisoni, F
Structural alerts for the identification of bioaccumulative compounds
2018 Valsecchi, C; Grisoni, F; Consonni, V; Ballabio, D
Detecting activity-rich structural regions by a new chemoinformatic approach: Mapping of Activity through Dichotomic Scores (MADS)
2018 Todeschini, R; Consonni, V; Ballabio, D; Grisoni, F
Artificial intelligence driven de novo molecular design for nuclear receptor ligand discovery
2018 Merk, D; Friedrich, L; Grisoni, F; Schneider, G
Scaffold hopping from synthetic RXR modulators by virtual screening and de novo design
2018 Merk, D; Grisoni, F; Friedrich, L; Gelzinyte, E; Schneider, G
Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability
2018 Focks, A; Grisoni, F; Barsi, A; Vighi, M
Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity
2018 Grisoni, F; Merk, D; Consonni, V; Hiss, J; Giani Tagliabue, S; Todeschini, R; Schneider, G
De Novo Design of Bioactive Small Molecules by Artificial Intelligence
2018 Merk, D; Friedrich, L; Grisoni, F; Schneider, G
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