Activities:

• Leading the development of a computational pipeline to analyze hybrid-capture long-read sequencing data.
• Analysis of genomic datasets, such as RNA-seq, ATAC-seq and Pacbio long-read SMRT-seq.
• Apply Machine Learning to identify RNA-based neoantigens for cancer immunotherapy.
• Mentoring of lab members including students and postdocs.
• Teaching R, Bioconductor and Genomics to scientists at JAX.

Activities:

• Research on T-acute lymphoblastic leukemia (T-ALL), a prevalent childhood blood cancer.
• Analysis of genomics data such as RNA-seq, Exome-seq and ChIP-seq.
• Analysis of mass spectrometry data (proteomics).
• Developed a methodology to identify active regulators from RNA-seq and ChIP-seq datasets, which lead to the discovery of a network of genes that initiate T cell leukemia.
• Developed a Shiny app to study pathway regulation in ChIP-seq data.

Activities:

• Developed methods to characterize the transcriptional and non-coding RNA networks in M. Tuberculosis (Mtb) during macrophage infection.
• Participated in TB PANNET Consortium (EU/USA), an international effort that carried out a comprehensive identification of non-coding RNAs in Mtb using a combination of custom microarrays and RNA-seq.
• Development of methods to identify targets and pathways regulated by cis-encoded and trans-encoded non-coding RNAs.

Activities:

• Reconstruction of Transcriptional Networks in Escherichia coli.
• Developed a neural network to predict motif structures in transcriptional networks.
• Analysis of microarrays for gene expression.

Activities:

• Application of Bayesian networks and partial correlation analysis for reconstruction of gene regulatory networks (protein-DNA interactions) in yeast
• Analysis of microarrays for gene expression.

Activities:

• Design and implementation of computational tools for modeling of metabolic and regulatory pathways using RDF graphs.
• Design and implementation of object-oriented XML databases for genomic data.

Activities:

• Linear Algebra and Analytical Geometry.