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Daniel Seeliger

5PUBLICATIONS
15CO-AUTHORS
Adversarial machine learningComputational chemistryBiomolecular modelling and designBiologically active molecules
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Journal

Publications (5)

Sort by Publication Date:
|Sep 02, 2021
ADMET Predictability at Boehringer Ingelheim: State-of-the-Art, and Do Bigger Datasets or Algorithms Make a Difference?

Stevan Aleksić, Daniel Seeliger, J B Brown

|Jun 04, 2021
Large scale relative protein ligand binding affinities using non-equilibrium alchemy.

Vytautas Gapsys, Laura Pérez-Benito, Matteo Aldeghi

|May 19, 2020
Hybrid Screening Approach for Very Small Fragments: X-ray and Computational Screening on FKBP51.

Sebastian W Draxler, Margit Bauer, Christian Eickmeier

|Apr 07, 2020
BIreactive: A Machine-Learning Model to Estimate Covalent Warhead Reactivity.

Ferruccio Palazzesi, Markus R Hermann, Marc A Grundl

|Aug 13, 2019
Fragment Binding Pose Predictions Using Unbiased Simulations and Markov-State Models.

Stephanie Maria Linker, Aniket Magarkar, Jürgen Köfinger

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Frequent Collaborators

1 joint publications

Aniket Magarkar

1 joint publications

Jürgen Köfinger

1 joint publications

Gerhard Hummer

1 joint publications

Ferruccio Palazzesi

1 joint publications

Christofer S Tautermann

1 joint publications

Alexander Weber

1 joint publications

Dennis Fiegen

1 joint publications

Vytautas Gapsys

1 joint publications

Laura Pérez-Benito

1 joint publications

Matteo Aldeghi

Frequent Collaborators

1 joint publications

Aniket Magarkar

1 joint publications

Jürgen Köfinger

1 joint publications

Gerhard Hummer

1 joint publications

Ferruccio Palazzesi

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