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
Discovery of Stomach Adenocarcinoma Biomarkers by Consensus..:
, In:
2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)
,
Chen, Ji
;
Hao, Yang
;
Wang, Tianjun
.. - p. 112-115 , 2022
Link:
https://doi.org/10.1109/ICBCB55259.2022.9802469
RT T1 <cTitle>2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)</cTitle>: T1 <Title>Discovery of Stomach Adenocarcinoma Biomarkers by Consensus Scoring of Random Sampling and Machine Learning Modeling</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9802469&Exemplar=1&LAN=DE A1 Chen, Ji A1 Hao, Yang A1 Wang, Tianjun A1 Huang, Daiyun A1 Liu, Xin YR 2022 K1 Support vector machines K1 Stomach K1 Genomics K1 Machine learning K1 Biomarkers K1 Predictive models K1 Bioinformatics K1 gastric cancer K1 stomach adenocarcinoma K1 machine learning K1 biomarker K1 support vector machine K1 SVM K1 recursive feature elimination K1 RFE SP 112 OP 115 LK http://dx.doi.org/https://doi.org/10.1109/ICBCB55259.2022.9802469 DO https://doi.org/10.1109/ICBCB55259.2022.9802469 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
