Genetic proxies for therapy of insulin drug targets and risk of osteoarthritis: a drug-target Mendelian randomization analysis
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Genetic proxies for therapy of insulin drug targets and risk of osteoarthritis: a drug-target Mendelian randomization analysis ; day:11 ; month:8 ; year:2024 ; pages:1-12
Inflammopharmacology ; (11.8.2024), 1-12
- Urheber
-
Cao, Ziqin
Li, Qiangxiang
Wu, Jianhuang
Li, Yajia
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s10787-024-01542-8
- URN
-
urn:nbn:de:101:1-2410292114446.705440058339
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:34 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Cao, Ziqin
- Li, Qiangxiang
- Wu, Jianhuang
- Li, Yajia
- SpringerLink (Online service)
Ähnliche Objekte (12)
Exploring drug-target interaction networks of illicit drugs
Lipid-lowering drugs and inflammatory bowel disease’s risk: a drug-target Mendelian randomization study
Drug–target interaction prediction via multiple classification strategies
Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study
Exploring the causal effect between lipid-modifying drugs and idiopathic pulmonary fibrosis: a drug-target Mendelian randomization study
Explainable deep drug–target representations for binding affinity prediction
Prediction of drug–target interactions through multi-task learning
DASPfind: new efficient method to predict drug–target interactions
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
Drug combinatorics and side effect estimation on the signed human drug-target network
New evidence: Metformin unsuitable as routine adjuvant for breast cancer: a drug-target mendelian randomization analysis
Assessing the safety of lipid-modifying medications among Chinese adolescents: a drug-target Mendelian randomization study
Exploring drug-target interaction networks of illicit drugs
Lipid-lowering drugs and inflammatory bowel disease’s risk: a drug-target Mendelian randomization study
Drug–target interaction prediction via multiple classification strategies
Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study
Exploring the causal effect between lipid-modifying drugs and idiopathic pulmonary fibrosis: a drug-target Mendelian randomization study
Explainable deep drug–target representations for binding affinity prediction
Prediction of drug–target interactions through multi-task learning
DASPfind: new efficient method to predict drug–target interactions
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
Drug combinatorics and side effect estimation on the signed human drug-target network
New evidence: Metformin unsuitable as routine adjuvant for breast cancer: a drug-target mendelian randomization analysis
Assessing the safety of lipid-modifying medications among Chinese adolescents: a drug-target Mendelian randomization study
Exploring drug-target interaction networks of illicit drugs
Lipid-lowering drugs and inflammatory bowel disease’s risk: a drug-target Mendelian randomization study
Drug–target interaction prediction via multiple classification strategies
Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study
Exploring the causal effect between lipid-modifying drugs and idiopathic pulmonary fibrosis: a drug-target Mendelian randomization study
Explainable deep drug–target representations for binding affinity prediction
Prediction of drug–target interactions through multi-task learning
DASPfind: new efficient method to predict drug–target interactions
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
Drug combinatorics and side effect estimation on the signed human drug-target network
New evidence: Metformin unsuitable as routine adjuvant for breast cancer: a drug-target mendelian randomization analysis