Projects citing the RC ressource

List of publication reusing Regulatory Circuits results (with more than 15 citations themselves), that motivated this RDFisation:

  1. Gao, L., Uzun, Y., Gao, P., He, B., Ma, X., Wang, J., Han, S., Tan, K.: Identifying noncoding risk variants using disease-relevant gene regulatory networks. Naturecommunications 9(1), 1–12 (2018)
  2. Horn, H., Lawrence, M.S., Chouinard, C.R., Shrestha, Y., Hu, J.X., Worstell, E.,Shea, E., Ilic, N., Kim, E., Kamburov, A., et al.: Netsig: network-based discovery from cancer genomes. Nature methods 15(1), 61 (2018)
  3. Jia, P., Han, G., Zhao, J., Lu, P., Zhao, Z.: Szgr 2.0: a one-stop shop of schizophrenia candidate genes. Nucleic acids research45(D1), D915–D924 (2017)
  4. Lomberk, G., Blum, Y., Nicolle, R., Nair, A., Gaonkar, K.S., Marisa, L., Mathison,A., Sun, Z., Yan, H., Elarouci, N., et al.: Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes. Nature communications 9(1), 1–10 (2018)
  5. Lòpez, C., Kleinheinz, K., Aukema, S.M., Rohde, M., Bernhart, S.H., Hübschmann,D., Wagener, R., Toprak, U.H., Raimondi, F., Kreuz, M., et al.: Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic burkitt lymphoma.Nature communications 10(1), 1–19 (2019)
  6. Noh, H., Shoemaker, J.E., Gunawan, R.: Network perturbation analysis of gene transcriptional profiles reveals protein targets and mechanism of action of drugs and influenza a viral infection. Nucleic acids research46(6), e34–e34 (2018)
  7. Paul, D.S., Teschendorff, A.E., Dang, M.A., Lowe, R., Hawa, M.I., Ecker, S., Beyan,H., Cunningham, S., Fouts, A.R., Ramelius, A., et al.: Increased dna methylation variability in type 1 diabetes across three immune effector cell types. Nature communications 7(1), 1–11 (2016)
  8. Saelens, W., Cannoodt, R., Saeys, Y.: A comprehensive evaluation of module detection methods for gene expression data. Nature communications 9(1), 1–12 (2018)
  9. Saelens, W., Cannoodt, R., Todorov, H., Saeys, Y.: A comparison of single-cell trajectory inference methods.Nature biotechnology37(5), 547–554 (2019)
  10. Vosa, U., Claringbould, A., Westra, H.J., Bonder, M.J., Deelen, P., Zeng, B.,Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., et al.: Unraveling the polygenic architecture of complex traits using blood eqtl meta-analysis. BioRxiv p447367 (2018)