My current projects are associated to facilitate my background in evolution and genomic analysis to define a platform called ''sciCNV'' for inferred chromosomal copy number variations (iCNVs) and to define characterizing scores that allows us to bioinformatically segregate tumor cells from non-tumor cells. We utilize a wide variety of information from our accumulated and fluorescence-activated cell sorting (FACS)-sorted patient samples including whole exome sequencing (WES), single-nucleotide polymorphism (SNP), single-nucleotide variations (SNV), DNA CNV analyses as well as tumor VDJ rearrangements to study diverse cell types. More precisely, using all these techniques we try to identify the signature genes, cancer initiating cells, genomic profiles and subclonal contents of tumor subpopulations in human MM.
Cancer Research & Evolutionary Dynamics
Machine Learning & Deep Learning
Mathematical Oncology & Computational Biology