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Sabina Smusz

Showing results (1-10 of 7) with videos related to

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Journal of Cheminformatics|April 9, 2013
The influence of the inactives subset generation on the performance of machine learning methodsSabina Smusz, Rafał Kurczab, Andrzej J Bojarski
Journal of Cheminformatics|July 1, 2014
The influence of negative training set size on machine learning-based virtual screeningRafał Kurczab, Sabina Smusz, Andrzej J Bojarski
Bioorganic & Medicinal Chemistry Letters|April 14, 2015
Fingerprint-based consensus virtual screening towards structurally new 5-HT(6)R ligandsSabina Smusz, Rafał Kurczab, Grzegorz Satała, et al.
Bioorganic & Medicinal Chemistry Letters|December 4, 2014
Exploiting uncertainty measures in compounds activity prediction using support vector machinesSabina Smusz, Wojciech Marian Czarnecki, Dawid Warszycki, et al.
Bioorganic & Medicinal Chemistry Letters|December 31, 2013
An application of machine learning methods to structural interaction fingerprints--a case study of kinase inhibitorsJagna Witek, Sabina Smusz, Krzysztof Rataj, et al.
Journal of Cheminformatics|May 8, 2015
Multiple conformational states in retrospective virtual screening - homology models vs. crystal structures: beta-2 adrenergic receptor case studyStefan Mordalski, Jagna Witek, Sabina Smusz, et al.
Journal of Chemical Information and Modeling|March 26, 2015
Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7)Sabina Smusz, Stefan Mordalski, Jagna Witek, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Journal of Cheminformatics|April 9, 2013
The influence of the inactives subset generation on the performance of machine learning methodsSabina Smusz, Rafał Kurczab, Andrzej J Bojarski
Journal of Cheminformatics|July 1, 2014
The influence of negative training set size on machine learning-based virtual screeningRafał Kurczab, Sabina Smusz, Andrzej J Bojarski
Bioorganic & Medicinal Chemistry Letters|April 14, 2015
Fingerprint-based consensus virtual screening towards structurally new 5-HT(6)R ligandsSabina Smusz, Rafał Kurczab, Grzegorz Satała, et al.
Bioorganic & Medicinal Chemistry Letters|December 4, 2014
Exploiting uncertainty measures in compounds activity prediction using support vector machinesSabina Smusz, Wojciech Marian Czarnecki, Dawid Warszycki, et al.
Bioorganic & Medicinal Chemistry Letters|December 31, 2013
An application of machine learning methods to structural interaction fingerprints--a case study of kinase inhibitorsJagna Witek, Sabina Smusz, Krzysztof Rataj, et al.
Journal of Cheminformatics|May 8, 2015
Multiple conformational states in retrospective virtual screening - homology models vs. crystal structures: beta-2 adrenergic receptor case studyStefan Mordalski, Jagna Witek, Sabina Smusz, et al.
Journal of Chemical Information and Modeling|March 26, 2015
Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7)Sabina Smusz, Stefan Mordalski, Jagna Witek, et al.
Pageof 1