The Administrative Core of this U19 collaborative research program will provide the administrative infrastructure required for the success of the program. Responsibilities of the Administrative Core include: facilitating coordination of efforts across the component research projects and the service cores; facilitating the exchange of information, viruses, samples and reagents between the different laboratories; facilitating and coordinate scientific interactions amongst the members involved in this U19 program; monitoring scientific progress and performance, resolving of technical problems and prioritizing models and experiments; monitoring and assuring timely achievement of all milestones and objectives; coordinating and facilitating interactions with NIAID, with the other Modeling Immunity for Biodefense (MIB) U19 centers and with the scientific community; organizing travel to NIAID for meetings of the Steering Committee; overseeing the dissemination and track the usage of models, data and other resources generated and compliance with the data- and model-sharing milestones and other resource sharing requirements of the MIB program; producing two workshops and two scientific symposia focused on computational modeling of immunity. In order to achieve this mission, we will continue the administrative practices we have refined in overseeing the current NIAID-contract supported MIB Program (PRiME) which we hope to continue in this proposed U19 program to accomplish the following service aims: Service Aim 1: To establish an organizational structure centered on an Executive Committee responsible for monitoring overall program progress and making decisions on staffing plans, allocation of resources, core usage and other policies. Service Aim 2: To coordinate conference calls and organize meetings between the PIs, selected key personnel, the Steering Committee and NIAID. Service Aim 3: To assist the investigators of this consortium in reagents, data and model sharing, manuscript preparations, public release of models and data and submission of annual progress reports to the NIH. Service Aim 4: To Provide Training and education in mathematical modeling of immunity.
| Medley, J Kyle; Choi, Kiri; König, Matthias et al. (2018) Tellurium notebooks-An environment for reproducible dynamical modeling in systems biology. PLoS Comput Biol 14:e1006220 |
| Nudelman, German; Frasca, Antonio; Kent, Brandon et al. (2018) High resolution annotation of zebrafish transcriptome using long-read sequencing. Genome Res 28:1415-1425 |
| D'Avola, Delia; Villacorta-Martin, Carlos; Martins-Filho, Sebastiao N et al. (2018) High-density single cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma. Sci Rep 8:11570 |
| Fribourg, M; Ni, J; Nina Papavasiliou, F et al. (2018) Allospecific Memory B Cell Responses Are Dependent on Autophagy. Am J Transplant 18:102-112 |
| Zhang, Liang; Wang, Juan; Muñoz-Moreno, Raquel et al. (2018) Influenza Virus NS1 Protein RNA-Interactome Reveals Intron Targeting. J Virol : |
| Zhou, Jian; Theesfeld, Chandra L; Yao, Kevin et al. (2018) Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk. Nat Genet 50:1171-1179 |
| Vodovotz, Yoram; Xia, Ashley; Read, Elizabeth L et al. (2017) Solving Immunology? Trends Immunol 38:116-127 |
| Martín-Vicente, María; Medrano, Luz M; Resino, Salvador et al. (2017) TRIM25 in the Regulation of the Antiviral Innate Immunity. Front Immunol 8:1187 |
| García-Sastre, Adolfo (2017) Ten Strategies of Interferon Evasion by Viruses. Cell Host Microbe 22:176-184 |
| Lavin, Yonit; Kobayashi, Soma; Leader, Andrew et al. (2017) Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses. Cell 169:750-765.e17 |
Showing the most recent 10 out of 29 publications
