Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/33985
DC FieldValueLanguage
dc.contributor.authorRroji, Meritaen_US
dc.contributor.authorSpasovski, Goceen_US
dc.date.accessioned2025-08-26T08:37:01Z-
dc.date.available2025-08-26T08:37:01Z-
dc.date.issued2025-06-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/33985-
dc.description.abstractOmics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of the current state and future prospects of integrating biomarkers into the clinical practice for CKD, aiming to improve patient outcomes by targeted therapeutic interventions. In fact, the integration of genomic, transcriptomic, proteomic, and metabolomic data has enhanced our understanding of CKD pathogenesis and identified novel biomarkers for an early diagnosis and targeted treatment. Advanced computational methods and artificial intelligence (AI) have further refined multi-omics data analysis, leading to more accurate prediction models for disease progression and therapeutic responses. These developments highlight the potential to improve CKD patient care with a precise and individualized treatment plan .en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofPROTEOMICSen_US
dc.titleOmics Studies in CKD: Diagnostic Opportunities and Therapeutic Potentialen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/pmic.202400151-
dc.identifier.urlhttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/pdf/10.1002/pmic.202400151-
dc.identifier.volume25-
dc.identifier.issue11-12-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptFaculty of Medicine-
Appears in Collections:Faculty of Medicine: Journal Articles
Прикажи едноставен запис

Google ScholarTM

Проверете

Altmetric


Записите во DSpace се заштитени со авторски права, со сите права задржани, освен ако не е поинаку наведено.