1 code implementation • 8 Jul 2022 • Matteo Manica, Jannis Born, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Dean Clarke, Yves Gaetan Nana Teukam, Giorgio Giannone, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang Han Hsu, Federico Zipoli, Oliver Schilter, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery.
1 code implementation • 5 Dec 2020 • Modestas Filipavicius, Matteo Manica, Joris Cadow, Maria Rodriguez Martinez
Less than 1% of protein sequences are structurally and functionally annotated.
1 code implementation • 27 May 2020 • Jannis Born, Matteo Manica, Joris Cadow, Greta Markert, Nil Adell Mill, Modestas Filipavicius, María Rodríguez Martínez
With the fast development of COVID-19 into a global pandemic, scientists around the globe are desperately searching for effective antiviral therapeutic agents.
no code implementations • 29 Aug 2019 • Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, Karsten Borgwardt, María Rodríguez Martínez
The generative process is optimized through PaccMann, a previously developed drug sensitivity prediction model to obtain effective anticancer compounds for the given context (i. e., transcriptomic profile).
no code implementations • 29 Mar 2018 • Matteo Manica, Joris Cadow, Roland Mathis, María Rodríguez Martínez
Reliable identification of molecular biomarkers is essential for accurate patient stratification.