miRNA-211 maintains metabolic homeostasis in medulloblastoma through its target gene long-chain acyl-CoA synthetase 4
December 19, 2023
Yuan, M., Mahmud, I., Katsushima, K., Joshi, K., Saulnier, O., Pokhrel, R., Lee, B., Liyanage, W., Kunhiraman, H., Stapleton, S., Gonzalez-Gomez, I., Kannan, R.M., Eisemann, T., Kolanthai, E., Seal, S., Garrett, T.J., Abbasi, S., Bockley, K., Hanes, J., Chapagain, P., Jallo, G., Wechsler-Reya, R.J., Taylor, M.D., Eberhart, C.G., Ray, A. & Perera, R.J. miRNA-211 maintains metabolic homeostasis in medulloblastoma through its target gene long-chain acyl-CoA synthetase 4. Acta Neuropathol Commun 11: 203 (2023). https://doi.org/10.1186/s40478-023-01684-w
The long non-coding RNA SPRIGHTLY and its binding partner PTBP1 regulate exon 5 skipping of SMYD3 transcripts in group 4 medulloblastomas
August 2, 2023
Lee, B., Katsushima, K., Pokhrel, R., Yuan, M., Stapleton, S., Jallo, G., Wechsler-Reya, R.J., Eberhart, C.G., Ray, A., and Perera, R.J. (2022). The long non-coding RNA SPRIGHTLY and its binding partner PTBP1 regulate exon 5 skipping of SMYD3 transcripts in group 4 medulloblastomas. Neuro-Oncology Advances 4, Issue 1 (2022) DOI: 10.1093/noajnl/vdac120
Machine learning in post-genomic biology
January 24, 2022
Ray, A. Machine learning in post-genomic biology. Data Mining Knowledge Discov. e1451 (2022) DOI: https://doi.org/10.1002/widm.1451
The paradoxical behavior of microRNA211 in melanomas and other human cancers
February 8, 2021
Ray, A. Kunhiraman, H, and Perera, R. The paradoxical behavior of microRNA211in melanomas and other human cancers. Front Oncol 10:628367 (2021) DOI: 3389/fonc.2020.628367
MicroRNA-211 modulates the DUSP6-ERK5 signaling axis to promote BRAFV600E-driven melanoma growth in vivo and BRAF/MEK inhibitor resistance
September 1, 2020
Lee, B., Sahoo, A., Mahmud, I., Sawada, J., Marchica, J., Sahoo, S., Layng,F.I.A.L., Finlay, D., Mazar, J., Joshi, P., Komatsu, M., Vuori, K., de Jong, R., Garrett, T., Ray, A., and Perera, R.J. MicroRNA-211 modulates the DUSP6-ERK5 signaling axis to promote BRAFV600E-driven melanoma growth in vivo and BRAF/MEK inhibitor resistance. J. Invest Dermatol 141: 385-394 (2021) https://doi.org/10.1016/j.jid.2020.06.038
Brahmachary’s contributions during the infancy of molecular embryology
September 1, 2020
Ray, A. Fields, Patterns and Information: R. L. Brahmachary’s contributions during the infancy of molecular embryology. J. Dev. Biol. 64: 35-40 (2020) doi: 10.1387/ijdb.190171ar
Supervised machine learning with protein structural and network topological features predicts physical interactors of the human Huntington’s disease protein
January 1, 2019
Lokhande, S., Koo, S. & Ray, A. Supervised machine learning with protein structural and network topological features predicts physical interactors of the human Huntington’s disease protein. In Proceedings of the IEEE International Conference on Computational Science and Computational Intelligence – International Society on Computational Biology (CSCI-ISCB’18) (2019). https://american-cse.org/csci2018/pdfs/CSCI2018-3OvSlHpbnpxVCh7wjFqa17/7ht0x0jlF6ti2iEcwm7ZHe/5D1IyF8caGwh7GwoGnrSse.pdf
The long noncoding RNA SPRIGHTLY acts as an intra-nuclear organizing hub for pre-mRNA molecules
May 3, 2017
Lee, B., Sahoo, A., Marchica1, J., Holzhauser, E., Chen, X., Li, J.-L., Seki, T., Govindarajan, S., Markey, F.B., Batish, M., Lokhande, S.J., Zhang, S., Ray, A. & Perera, R.J. The long noncoding RNA SPRIGHTLY acts as an intra-nuclear organizing hub for pre-mRNA molecules. Science Adv 3: e1602505 May 3 (2017). https://doi.org/10.1126/sciadv.1602505
A genome wide dosage suppressor network reveals genomic robustness
November 28, 2016
Patra, B.N., Kon, Y., Yadav, G., Sevold, A., Frumkin, J.P., Vallabhajosyula, R.R., Hintze, A., Østman, B., Schosseau, J., Bhan, A., Marzolf, B., Tamashiro, J.K., Kaur, A., Baliga, N.S., Grayhack, E.J., Galas, D.J., Raval, A., Adami, C., Phizicky, E.M. & Ray, A. A genome wide dosage suppressor network reveals genomic robustness. Nucl Acids Res 45 (1): 255-270 (2017). DOI: https://doi.org/10.1093/nar/gkw1148
A link between chromatin condensation mechanisms and Huntington’s disease: Connecting the dots
September 22, 2016
Lokhande, S.T., Patra, B.N. & Ray, A. A link between chromatin condensation mechanisms and Huntington’s disease: Connecting the dots. BioSyst. 12, 3515-3529 (2016) DOI: https://doi.org/10.1039/C6MB00598E
The interplay between chromosome stability and cell cycle control explored through gene–gene interaction and computational simulation
August 16, 2016
Frumkin, J.P., Patra, B.N., Sevold, A., Ganguly, K., Patel, C., Yoon, S., Schmid, M.B. & Ray, A. The interplay between chromosome stability and cell cycle control explored through gene–gene interaction and computational simulation. Nucl Acids Res 44 (17): 8073-8085 (2016) DOI: https://doi.org/10.1093/nar/gkw715
miR-211 functions as a metabolic switch in human melanoma cells
January 12, 2016
Mazar J, Qi F, Lee B, Marchia J, Govindarajan S, Shelley J, Li JL, Ray A, Perera RJ. miR-211 functions as a metabolic switch in human melanoma cells. Mol Cell Biol 36:1090–1108 (2016). doi:1128/MCB.00762-15.
A signature of power law network dynamics
April 9, 2014
Bhan, A. and Ray, A. A signature of power law network dynamics. BioRxiv doi: http://dx.doi.org/10.1101/004028 (2014)
Genome-wide methylated CpG island profiles of melanoma cells reveal a melanoma coregulation network
April 9, 2014
J-L Li, J Mazar, C Zhong, GJ Faulkner, SS Subramaniam, S Govindarajan, Z Zhang, ME Dinger, G Meredith, C Adams, S Zhang, JS Mattick, A Ray*, and RJ Perera*. Genome-wide methylated CpG island profiles of melanoma cells reveal a melanoma coregulation network. Nature Sci. Report 3: 2962 (https://www.nature.com/articles/srep02962) (2013) (*Corresponding authors)
Polyglutamine disease modeling: Epitope based screen for homologous recombination using CRISPR/Cas9 System
January 1, 2014
An MC, O’Brien RN, Zhang N, Patra BN, De La Cruz M, Ray A, Ellerby LM. Polyglutamine disease modeling: Epitope based screen for homologous recombination using CRISPR/Cas9 System. PloS Curr. doi: https://doi.org/10.1371/currents.hd.0242d2e7ad72225efa72f6964589369a (2014)