Integrative data analytic framework to enhance cancer precision medicine
Visualitza/Obre
Cita com:
hdl:2117/350960
Tipus de documentArticle
Data publicació2021-03
EditorMary Ann Liebert, Inc., publishers
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement 3.0 Espanya
Abstract
With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.
Document relacionathttps://life.bsc.es/iconbi/context_aware_embeddings/index.html
CitacióGaudelet, T.; Malod Dognin, N.; Przulj, N. Integrative data analytic framework to enhance cancer precision medicine. "Network and Systems Medicine", Març 2021, vol. 4, núm. 1, p. 60-73.
ISSN2690-5949
Versió de l'editorhttps://www.liebertpub.com/doi/10.1089/nsm.2020.0015
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
nsm.2020.0015.pdf | 689,2Kb | Visualitza/Obre |