k_algorithms 699 B

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  1. %SUMMARY
  2. %- ABSTRACT
  3. %- INTRODUCTION
  4. %# BASICS
  5. %- \acs{DNA} STRUCTURE
  6. %- DATA TYPES
  7. % - BAM/FASTQ
  8. % - NON STANDARD
  9. %- COMPRESSION APPROACHES
  10. % - SAVING DIFFERENCES WITH GIVEN BASE \acs{DNA}
  11. % - HUFFMAN ENCODING
  12. % - PROBABILITY APPROACHES (WITH BASE?)
  13. %
  14. %# COMPARING TOOLS
  15. %-
  16. %# POSSIBLE IMPROVEMENT
  17. %- \acs{DNA}S STOCHASTICAL ATTRIBUTES
  18. %- IMPACT ON COMPRESSION
  19. \section{Compression aproaches}
  20. Several algorithms for data compression, have been prooven efficient over the last decades. The well known Huffman coding, is used in several Tools for genome compression (genomic squeeze <- offizial | inofficial -> GDC, GRS).
  21. further algos
  22. - (r)ANS Arithmetik numeral systems
  23. - Arithmetic encoding