Genomics Algorithms: Try again! Fail again!! Fail Better!!!

Bud Mishra

We will describe a new approach to genomics problems based on a new technology: Nano Mapping, which is ultra-cheap, fast (low latency/high throughput), accurate and potentially highly disruptive. As the genomic analyses of humans have continued to gain momentum (ancestry.com, 23andMe, etc.), we are frustrated by the problem of not being able to accurately create and interpret data that reflect the genome‚Äôs true complexity: in tumor analysis (single cell/single molecule), microbiomics, liquid biopsy (circulating tumor cells and cell free DNA), epigenetics, etc. The new technology addresses these issues. The talk will focus on various computational and complexity theoretic questions related to data analyses and their applications: Solving instances of NP-hard problems associated with Variant Detection, Haplotype Phasing, Whole Genome Off-target analysis (e.g., with CRISPR assays), Sequence Assembly, etc. And doing so in Polynomial time (so-called NP-easy problems) or even in Polylog/Constant time (using hashing and hardware acceleration). 


Bud Mishra, Professor Courant Institute (NYU)

Jointly with J Reed.

See also: https://www.nature.com/articles/s41467-017-01891-9.pdf