Biological systems are fundamentally multi-scale, with mostly uncharacterized molecular pathways, cellular actions, and cellular communities that collectively give rise to their function. While one high-throughput measurement technology can resolve specific biological molecules, comprehensive characterization of biological systems can only be achieved by integration of multi-modal data types across molecular, cellular, spatial, and population scales. The integration of heterogeneous and complementary assays from multi-omics can reveal interactions between modalities that drive biological systems and processes. Recent advances in single-cell multi-omics technologies provide unprecedented opportunities for such multi-scale characterization but interpreting biological processes from these data requires parallel advances in novel computational techniques.
Community-wide hackathons to identify central themes in single-cell multi-omics / Kim-Anh Lê, Cao; Al J., Abadi; Emily F., Davis-Marcisak; Lauren, Hsu; Arshi, Arora; Alexis, Coullomb; Atul, Deshpande; Yuzhou, Feng; Pratheepa, Jeganathan; Melanie, Loth; Chen, Meng; Wancen, Mu; Vera, Pancaldi; Kris, Sankaran; Righelli, D; Amrit, Singh; Joshua S., Sodicoff; Genevieve L., Stein-O’Brien; Ayshwarya, Subramanian; Joshua D., Welch; Yue, You; Ricard, Argelaguet; Vincent J., Carey; Ruben, Dries; Casey S., Greene; Susan, Holmes; Michael I., Love; Matthew E., Ritchie; Guo-Cheng, Yuan; Aedin C., Culhane; Elana, Fertig. - In: GENOME BIOLOGY. - ISSN 1474-760X. - 22:1(2021), pp. 1-21. [10.1186/s13059-021-02433-9]
Community-wide hackathons to identify central themes in single-cell multi-omics
Righelli D;
2021
Abstract
Biological systems are fundamentally multi-scale, with mostly uncharacterized molecular pathways, cellular actions, and cellular communities that collectively give rise to their function. While one high-throughput measurement technology can resolve specific biological molecules, comprehensive characterization of biological systems can only be achieved by integration of multi-modal data types across molecular, cellular, spatial, and population scales. The integration of heterogeneous and complementary assays from multi-omics can reveal interactions between modalities that drive biological systems and processes. Recent advances in single-cell multi-omics technologies provide unprecedented opportunities for such multi-scale characterization but interpreting biological processes from these data requires parallel advances in novel computational techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
