Improved graph‐based multitask learning model with sparse sharing for quantitative structure–property relationship prediction of drug molecules-Reference-Cited by-同舟云学术

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Improved graph‐based multitask learning model with sparse sharing for quantitative structure–property relationship prediction of drug molecules

Published:2022-11-29 Issue:2 Volume:69 Page:
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE Journal

Author:

Hu Haoyang¹,Bai Yunke¹,Yuan Zhihong¹^ORCID

Affiliation:

1. State Key Laboratory of Chemical Engineering, Department of Chemical Engineering Tsinghua University Beijing China

Funder

Department of Science and Technology of Shandong Province

Ministry of Science and Technology of the People's Republic of China

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aic.17968

Reference60 articles.

1. How to improve R&D productivity: the pharmaceutical industry's grand challenge

2. Innovation in the pharmaceutical industry: New estimates of R&D costs

3. The art and practice of structure-based drug design: A molecular modeling perspective

4. De novo drug design framework based on mathematical programming method and deep learning model

5. Computer-aided molecular design of solvents for chemical separation processes

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2. Chemical space deconstruction-based dynamic model ensemble architecture for molecular property prediction;Chemical Engineering Science;2024-08

3. In Silico Prediction of the Temperature-Dependent Decomposition Rate Coefficients of Symmetrical Azo Compounds;Industrial & Engineering Chemistry Research;2023-09-21

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