Future movie and gaming industries will employ more and more accurate and numerically reliable methods for animations and rendering. These methods, for instance the Finite Element Method (FEM), are employed for not only for entertainment, but also for simulating old and new materials, applying different physics such as Neo-Hookean mechanics for key-frame animations or Navier-Stokes equations for fluid mechanics in physical engines (e.g., fog, water, air), or a mixture of methods for interacting bodies.
Third-generation mobile genetic sequencing technologies, including Oxford Nanopore's MinION and SmidgION, fit in the palm of a hand and only require a USB outlet. Unfortunately, the development of data analysis tools for these technologies is in a nascent stage, impeding on the portability of these devices. We need to address scalability and portability issues, producing software that can, from a smartphone to a workstation, perform efficiently with devices sporting limited RAM.
These projects are no longer maintained.
This work presents a novel error correction algorithm based on k-mer strings with their associated overlap graph, along with an open-source, multi-threaded, implementation. The algorithm, named HErCoOl (High-throughput Error Correction by Oligomers), needs minimal tuning, only an overall error rate and—optionally—information about the genome sizes.
This work proposes an error correction method based on the deBruijn graph that permits its execution on GB-sized data sets using normal desktop computers. The implementation makes use of hashing techniques, and implements an A* algorithm for error correction, minimizing the distance between an erroneous read and its replacement with the Needleman-Wunsch score.