51 citations · 79 across the 4 of their papers we have counts for
5 papers
Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions
Vladimir Golkov, Alexander Becker, Daniel T. Plop +6
Computer-aided drug discovery is an essential component of modern drug development. Therein, deep learning has become an important tool for rapid screening of billions of molecules…
An Empirical Bayes Approach to Regularization Using Previously Published Models
Derek K Smith, Loren E Smith, Brett Kroncke +3
This manuscript proposes a novel empirical Bayes technique for regularizing regression coefficients in predictive models. When predictions from a previously published model are ava…
3D Deep Learning for Biological Function Prediction from Physical Fields
Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev +5
Predicting the biological function of molecules, be it proteins or drug-like compounds, from their atomic structure is an important and long-standing problem. Function is dictated…
Protein structure prediction guided by cross-linking restraints - A systematic evaluation of the impact of the cross-linking spacer length
Tommy Hofmann, Axel W. Fischer, Jens Meiler +1
Recent development of high-resolution mass spectrometry (MS) instruments enables chemical cross-linking (XL) to become a high-throughput method for obtaining structural information…
BCL::MP-Fold: membrane protein structure prediction guided by EPR restraints
Axel Walter Fischer, Nathan Scott Alexander, Nils Woetzel +3
For many membrane proteins the determination of their topology remains a challenge for methods like X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. Electro…