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 Model Based on Insulin Resistance Metagene..:
Aditya Saxena
;
Nitish Mathur
;
Pooja Pathak
..
Biomacromolecules: Carbohydrates. , 2023
Link:
https://doi.org/10.3390/biom13030432
RT Journal T1
Machine Learning Model Based on Insulin Resistance Metagenes Underpins Genetic Basis of Type 2 Diabetes
UL https://suche.suub.uni-bremen.de/peid=base-ftmdpi:oai:mdpi.com:_2218-273X_13_3_432_&Exemplar=1&LAN=DE A1 Aditya Saxena A1 Nitish Mathur A1 Pooja Pathak A1 Pradeep Tiwari A1 Sandeep Kumar Mathur PB Multidisciplinary Digital Publishing Institute YR 2023 K1 insulin resistance (IR) K1 type 2 diabetes (T2D) K1 machine learning K1 GSEA K1 artificial neural network K1 HOMA-IR K1 HOMA-B K1 GWAS JF Biomacromolecules: Carbohydrates LK http://dx.doi.org/https://doi.org/10.3390/biom13030432 DO https://doi.org/10.3390/biom13030432 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)