Table of Contents

PREFACE
CHAPTER 1 SOME BIOLOGICAL CONCEPTS 1
1.1 Cell 1
1.2 Genetic Material: DNA，Gene and RNA 1
1.2.1 DNA 1
1.2.2 Gene 3
1.2.3 RNA 5
1.3 Protein and Amino Acids 7
1A Chromosome 9
1.5 Omics 10
1.5.1 Genomics 11
1.5.2 Microarray 11
1.5.3 Proteomics 11
1.5.4 Lipidomics 12
REFERENCES 13
CHAPTER 2 GRAPHICAL REPRESENTATIONS OF DNA SEQUENCE .14
2.1 Three-Dimension (3-D) Graphical Representation 14
2.2 2-D Graphical Representation 15
2.3 2-D Graphical Representations Without Degeneracy 17
2.4 Used a 1-D Numerical Representation of four Nucleotides to Construct a 2-D Graphical Representation of the DNA Sequence 22
REFERENCES 22
CHAPTER 3 NUMERICAL REPRESENTATIONS OF DNA SEQUENCE 24
3.1 4-D and 3-D Numerical Representations of a DNA Sequence 24
3.2 2-D Numerical Representations of a DNA Sequence 25
3.3 The Complex Numerical Representation 26
3.4 1-D Numerical Representations of four Nucleotides and 2-D Graphical Representation of a DNA Sequence 27
3.5 The Representations of Feature Vector, Genome Space and Matrix Representation of DNA Sequence 27
3.6 The Numerical Representation Based on Physical, Chemical and Structural Properties of DNA Sequence 29
3.6.1 The numerical representations based on some attribute equivalences of nucleotides 29
3.6.2 The representation of DNA by the inspiration from codon and the idea of three attribute equivalences 31
3.6.3 EIIP numerical representation for nucleotides 31
REFERENCES 32
CHAPTER 4 NUMERICAL REPRESENTATIONS OF PROTEIN 33
4.1 1-D Numerical and Graphical Representadons of the Amino Acid Sequence 33
4.2 2-D Numerical and Graphical Representations of the Amino Add Sequence 34
4.3 A 2-D Graphical Representation and Moment Vector Representation of Protein 41
4.4 3-D Numerical Representation of Protein 44
4.5 The 10-D Representation of an Amino Acid 45
4.6 The Vector and Matrix Representations of Protein Sequence and Protein Space . 46
4.7 Other Schemes of the Representation for Protein 46
REFERENCES 47
CHAPTER 5 PRACTICAL ORTHOGONAL TRANSFORM 49
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12.4.1 Least squares estimate of the unknown variable 190
12.4.2 The least square estimation of missing data based on genes 191
12.4.3 The least square estimation of missing data based on arrays 192
12.4.4 Combining the gene and array based estimates 192
12.5 Local Least Square Inputting (LLSinpute) 193
12.5.1 Selecting genes 194
12.5.2 Gene-wise formulation of local least squares imputation 195
12.6 The Comparison of the Methods of Missing Data Inputting 197
REFERENCES 199
PLATE