Title:	Model training for Optical DNA mapping
DNr:	NAISS 2024/22-957
Project Type:	NAISS Small Compute
Principal Investigator:	Albertas Dvirnas <albertas@chalmers.se>
Affiliation:	Chalmers tekniska högskola
Duration:	2024-06-28 – 2025-07-01
Classification:	10203
Homepage:	https://github.com/dnadevcode/
Keywords:

Abstract

We will use the computing resources to train the parameters for the various models in the field of Optical DNA mapping. These include the fitting of the binding constants for the competitive binding model (HCA), parameters for the kymograph alignment (SPALIGN), optimal parameters for local alignment algorithm (MP) and structural variation detection (HMMSV).