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1 Chapter 1Table 1.1 The total number of known species.Table 1.2 Extreme sizes of unicellular organisms.Table 1.3 Extreme sizes in viruses.Table 1.4 Single-celled organisms vs. viruses.

2 Chapter 2Table 2.1 The average genome size in the tree of life.Table 2.2 The average genome size in prokaryotes.Table 2.3 The average genome size in different eukaryotic organelles.Table 2.4 The average DNA length of different plasmids.Table 2.5 The average genome size of different eukaryotic and prokaryotic viruse...Table 2.6 Genes vs. proteins in the tree of life.

3 Chapter 3Table 3.1 Traceback start and stop locations.

4 Chapter 4Table 4.1 Global alignment and Local alignment.Table 4.2 Examples of alignments and associated scores.Table 4.3 The significance thresholds based on TRNG and MCG. Table 4.4 Forced alignment and local alignment.Table 4.5 RIK examples for one multivalue record from local storage.

5 Chapter 5Table 5.1 An intuitive step-by-step calculation example.Table 5.2 A signal extraction based on local information content.Table 5.3 A convergence test of the local regime for sliding windows of differen...

6 Chapter 6Table 6.1 Additional experiments on frequencies.

7 Chapter 8Table 8.1 Examples of DNA motifs.Table 8.2 Splicing motifs from human genes.

8 Chapter 9Table 9.1 A set of motifs.Table 9.2 Examples of alphabets for different sequences.Table 9.3 The fate of a PPM value.Table 9.4 Sets of variations for null models.Table 9.5 The null model in PPM format.Table 9.6 Motif set vs. consensus.Table 9.7 Examples of pseudo-counts and their effects on the negative scale.

9 Chapter 10Table 10.1 Additional tests by using pseudo-counts.Table 10.2 The meaning of scores.Table 10.3 Range of values for scores.

10 Chapter 11Table 11.1 Scanner discrimination power.Table 11.2 Signal filters and thresholds.

11 Chapter 12Table 12.1 Tests performed with pseudo-counts and two PFMs (real background).Table 12.2 Additions to the background set.Table 12.3 Tests performed on a scanner with two PFMs.Table 12.4 Detection and contrast.Table 12.5 Information content and score values.

12 Chapter 13Table 13.1 Transition matrices and specially constructed sequences.

13 Chapter 14Table 14.1 The meaning of scores.

14 Chapter 15Table 15.1 Results of the two halves of the spectral forecast equation.Table 15.2 Experiments on the spectral forecast equation by using a single matri...Table 15.3 Experiments on the spectral forecast equation by using two different ...Table 15.4 Set up for example 1.Table 15.5 Step-by-step calculation for example 1.Table 15.6 Set up for example 2.Table 15.7 Step-by-step calculation for example 2.Table 15.8 Set up for example 3.Table 15.9 Step-by-step calculation for example 3.

15 Chapter 16Table 16.1 Information entropy vs. information content.

16 Chapter 17Table 17.1 A link between entropy, information, patterns, and the perception of ...

Algorithms in Bioinformatics

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