I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Machine Learning-Driven Drug Discovery: Fast Prediction of ..:
, In:
2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
,
Mashkin, Ivan
;
Feng, Fan
;
Li, Zishen
... - p. 43-44 , 2023
Link:
https://doi.org/10.1109/IEEECONF58974.2023.10404738
RT T1
2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
: T1
Machine Learning-Driven Drug Discovery: Fast Prediction of Binding Property with Molecular Sub-Structures Analysis
UL https://suche.suub.uni-bremen.de/peid=ieee-10404738&Exemplar=1&LAN=DE A1 Mashkin, Ivan A1 Feng, Fan A1 Li, Zishen A1 Yau, Wai Yin A1 Lui, Leong-Ting A1 Au-Yeung, Ho Yu A1 Chan, Rosa H. M. YR 2023 K1 Drugs K1 Sodium K1 Medical services K1 Predictive models K1 Transformers K1 Ions K1 Task analysis SP 43 OP 44 LK http://dx.doi.org/https://doi.org/10.1109/IEEECONF58974.2023.10404738 DO https://doi.org/10.1109/IEEECONF58974.2023.10404738 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)