PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks-Reference-Cited by-同舟云学术

PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks

Published:2018-12-26 Issue:3 Volume:59 Page:1172-1181
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Jiménez José¹^ORCID,Sabbadin Davide¹,Cuzzolin Alberto²,Martínez-Rosell Gerard²,Gora Jacob³⁴,Manchester John³,Duca José³,De Fabritiis Gianni¹²⁵^ORCID

Affiliation:

1. Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer del Dr. Aiguader 88, 08003, Barcelona, Spain

2. Acellera, Barcelona Biomedical Research Park (PRBB), Carrer del Dr. Aiguader 88, 08003, Barcelona, Spain

3. Global Discovery Chemistry, Novartis Institutes for Biomedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States

4. Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany

5. Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain

Funder

European Regional Development Fund

Ministerio de Econom?a y Competitividad

Horizon 2020 Framework Programme

Acellera Ltd.

Publisher

American Chemical Society (ACS)

Subject

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

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00711

Reference59 articles.

1. Can the pharmaceutical industry reduce attrition rates?

2. Current Challenges and Trends in the Discovery of Agrochemicals

3. Chemical Space: Big Data Challenge for Molecular Diversity

4. Comparison of human cell signaling pathway databases—evolution, drawbacks and challenges

5. Prediction of compounds’ biological function (metabolic pathways) based on functional group composition

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