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Alberto Riva

Bioinformatics Scientific Director

(352) 294-5475
ariva@ufl.edu
191 CGRC

Bio

I am a bioinformatics scientist with an extensive background in computer science, knowledge engineering, computational biology and biomedical informatics. In the course of my career I have been able to apply my technical and scientific skills to a large number of domains and problems, ranging from telemedicine to patient data security, from genomics and transcriptomics to association studies for complex diseases, from molecular genetics to population studies. I have developed a large number of databases, software tools, web-based resources, and computational methods, based on the concept that integrating diverse data from multiple sources and making them easily available to researchers can provide substantial benefits to the progress of scientific research. In my current position at the UF ICBR Bioinformatics Core I am mainly responsible for the analysis of NGS datasets using high-performance computing, in addition to providing consultation and expert advice on the use of computational methods in biomedical research.

Skills and Specialization

  • Bioinformatics
  • High-performance computing, software and database development
  • Computational biology

Selected Publications

  1. Bennett RL, Bele A, Small EC, Will CM, Nabet B, Oyer JA, Huang X, Ghosh RP, Grzybowski AT, Yu T, Zhang Qiao, Riva A, Lele TP, Schatz GC, Kelleher NL, Ruthenburg AJ, Liphardt J, Licht JD. A Mutation in Histone H2B Represents a New Class of Oncogenic Driver. Cancer Discovery. 2019 doi:10.1158/2159-8290.CD-19-0393.
  2. Moumne O, Chowdhury R, Doll C, Pereira N, Hashimi M, Grindrod T, Dollar J, Riva A, Kasahara H. Mechanism sharing between genetic and gestational hypoxia-induced cardiac anomalies. Frontiers in Cardiovascular Medicine. 2018; 5:100; doi:10.3389/fcvm.2018.00100.
  3. Ezponda T, Dupéré-Richer D, Will CM, Small EC, Varghese N, Patel T, Nabet B, Popovic R, Oyer J, Bulic M, Zheng Y, Huang X, Shah MY, Maji S, Riva A, Occhionorelli M, Tonon G, Kelleher N, Keats J, Licht JD. UTX/KDM6A Loss Enhances the Malignant Phenotype of Multiple Myeloma and Sensitizes Cells to EZH2 inhibition. Cell Rep. 2017 Oct 17;21(3):628-640. PubMed: 29045832; doi:10.1016/j.celrep.2017.09.078.
  4. Nabilsi NH, Deleyrolle LP, Darst RP, Riva A, Reynolds BA, Kladde MP. Multiplex mapping of chromatin accessibility and DNA methylation within targeted single molecules identifies epigenetic heterogeneity in neural stem cells and glioblastoma. Genome Research. 2014 Feb;24(2):329-39. PubMed: 24105770.
  5. Riva A. Large-scale computational identification of regulatory SNPs with rSNP-MAPPER. BMC Genomics. 2012 Jun 18;13 Suppl 4:S7. PMID: 22759655.

Social Presence

Twitter: @AlbertoRivaUF