VirtualPlant: An integrated database and webserver that allows users to analyze their microarray results in the context of other publicly available functional genomic data

  • VirtualPlant has over 1,000 registered users from over 42 countries and has been cited by 42 manuscripts in peer-reviewed journals.
  • VirtualPlant enables Biologists to analyze genomic data in a user-friendly web interface where their dataset can be saved in a GeneCart and accessed at any point.
  • VirtualPlant is an international collaboration between the VirtualPlant group in Chile and the group at NYU.

Identification of Biomarkers for Brown Streak Disease susceptible Cassava using Next-generation sequencing data

  • In collaboration with Morag Ferguson (ILRI, Nairobi, Kenya)
  • Funded by Bill and Melinda Gates Foundation
  • Identified differentially expressed genes in resistant and susceptible Cassava ecotypes by analyzing RNA-seq data from infected and un-infected leaves.
  • Identified candidate SNPs associated with resistance to virus by analyzing draft sequences from related Cassava ecotypes
  • Comparative genomics analysis of virus resistant relatives of Cassava to identify region of recent adaptations.

Enabling individualized therapy for Prostate Cancer Patients

  • In Collaboration with Dr. Alex Rai (Columbia University Department of Pathology)
  • Developed biomarker discovery pipeline using R for high-throughput gene expression and proteomic array data analysis.
  • Employed this tool to identify candidate biomarker signatures for separating aggressive vs. indolent prostate cancers, using both supervised and unsupervised bioinformatics approaches.

Bioinformatics Group Manager

  • Supervise scientific programmers from Computer Science and Biology backgrounds with broad range of expertise, Bachelors, Masters, and PhDs Bioinformatics Support to Biologists
  • Collaborations have resulted in 13 publications in peer-reviewed journals.
  • Publications include analysis of RNA-seq, CHIP-seq, and Microarray datasets in a systems biology context.
  • Created a gene network (Multinetwork) by integrating publicly available interaction data such as Protein-Protein interaction from AtPID and literature, Transcription Regulatory interactions from AGRIS and literature, Metabolic pathways from KEGG and Aracyc, miRNA interactions from mirBASE and ASRP.