Druggability Assessment in TRAPP Using Machine Learning Approaches-Reference-Cited by-同舟云学术

Druggability Assessment in TRAPP Using Machine Learning Approaches

Author:

Yuan Jui-Hung¹²,Han Sungho Bosco¹³,Richter Stefan¹,Wade Rebecca C.¹²³⁴^ORCID,Kokh Daria B.¹^ORCID

Affiliation:

1. Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany

2. Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, 69120 Heidelberg, Germany

3. Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany

4. Zentrum für Molekulare Biologie (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, 69120 Heidelberg, Germany

Funder

European Commission

Klaus Tschira Stiftung

European Federation of Pharmaceutical Industries and Associations (Innovative Medicines Initiative)

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

Reference47 articles.

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