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https://github.com/m4tx/masters-thesis
Implementation of Context Binning and Model Clustering for Compression of Genetic Data
https://github.com/m4tx/masters-thesis
compression genetic-data latex thesis
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Implementation of Context Binning and Model Clustering for Compression of Genetic Data
- Host: GitHub
- URL: https://github.com/m4tx/masters-thesis
- Owner: m4tx
- License: cc-by-sa-4.0
- Created: 2022-09-02T20:33:03.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2023-07-13T19:12:05.000Z (over 1 year ago)
- Last Synced: 2024-11-11T04:36:02.523Z (3 months ago)
- Topics: compression, genetic-data, latex, thesis
- Language: TeX
- Homepage:
- Size: 60.5 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Implementation of Context Binning and Model Clustering for Compression of Genetic Data
My master's thesis written as part of the computer science course at Jagiellonian University.
## Abstract
In recent years, there happened a gigantic leap in the speed of DNA sequencing
methods, which allowed us to sequence DNAs of complex organisms, such as humans,
quickly. However, this leads to increasing demand for disk storage, as the
sizes of the databases containing such data can easily reach dozens of
terabytes. In his article "Context binning, model clustering and adaptivity
for data compression of genetic data", Jarek Duda proposes promising compression
techniques that should help build a compressor better than the current state of
the art. This thesis describes the compressor built to evaluate those
techniques, tests it with real-world data and compares it to other genetic data
compression tools.## Download
The PDF file can be downloaded from the
[GitHub Releases page](https://github.com/m4tx/masters-thesis/releases/download/final/Implementation_of_Context_Binning_and_Model_Clustering_for_Compression_of_Genetic_Data.pdf).## Building
Make sure you have Inkscape and a distribution of LaTeX installed in your
system.```bash
make
```## License
This work is licensed under a
[Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/).