A Toy Model of Chemical Reaction Networks - TBI - UniversitÃ¤t Wien

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24 CHAPTER 3. MOLECULES digit ::= [’0’-’9’] Mantissa ::= empty | ’E’ sign digit instring ::= ASCII - {\&,"} | \& character+ ; whitespace ::= space | tabulator | newline Here, graphs are encoded by blocks starting with the keyword graph. Inside this block, nodes and edges are defined by key-value list using the keywords node and edge. The following example shows how their attributes are defined: # Isobutane graph [ node [ id 1 label "C" ] node [ id 2 label "C" ] node [ id 3 label "C" ] node [ id 4 label "C" ] ] edge [ source 1 target 2 label "-" ] edge [ source 1 target 3 label "-" ] edge [ source 1 target 4 label "-" ] Labels of atoms and bonds define their type, i.e. C, N, or O for atoms, and − (single), = (double), or # (triple) for bonds. The GML format is precise and non-redundant, but long and tiresome to read. Thus, a different format is need for quickly displaying lists of molecules. SMILES (Simplified Molecular Input Line Entry Specification) 1 is a line notation, i.e. a string representation for molecules. SMILES are compact and their grammar is easy to learn. Their similarity to structural formulae makes their grammar intuitive for chemists. Moreover, in order to eliminate duplicates from a list of molecules or to subtract one list of molecules from another, as in sect. 5.1, a comparison of the structural formulae must be performed. This amounts to a test of graph isomorphism, for which neither an efficient algorithm nor proof of NPcompleteness is known in general [72]. The chemically relevant problem of testing graph isomorphism with bounded vertex degree (bounded valency of the atoms), however, can be solved in polynomial time [77]. We transform the molecular graphs into their canonical SMILES representation [120, 121]. The isomorphism test then reduces to simple string comparison. 1 from http://www.daylight.com/smiles/f smiles.html: “SMILES originated in the depths of the US government, where humorous names for things are frowned upon unless they are acronyms.”
3.3. CHEMICAL STRUCTURE REPRESENTATION 25 CH 4 C or C(H)(H)(H)H H 3 C CH 3 CC or C(H)(H)(H)C(H)(H)(H) CC(C)C or C(H)(H)(H)C(H)(C(H)(H)(H))C(H)(H)(H) OH OC(C = C1) = CC = C1 or HOC(C(H) = C1H) = C(H)C(H) = C1H Figure 3.6: An extremely brief SMILES tutorial. The BNF notation of the subset of SMILES used in the Toy Model is: atom ::= ’C’ | ’N’ | ’O’ | ’H’ bond ::= | ’-’ | ’=’ | ’#’ chain ::= | branch ::= ’(’ ’)’ | ’(’ ’)’ | ’(’ ’)’ | ’(’ ’)’ smiles ::= | In addition to these rules, which describe trees, cycles are indicated by adding identical digits to the atoms closing a cycle. Hydrogen atoms may be included implicitly or explicitly. See fig. 3.6 for a quick list of examples. The canonical SMILES are built using rules described in [121]. First a graph data structure with canonical labeling and ranking is built, ordered according to the labels and ranks. Then a unique SMILES is generated,
Page 1 and 2: A Toy Model of Chemical Reaction Ne
Page 3: i Dank an alle, die zum Gelingen di
Page 7: v Zusammenfassung Chemische Reaktio
Page 10 and 11: viii CONTENTS B GRW 61 C Organic re
Page 12 and 13: 2 CHAPTER 1. INTRODUCTION ▽ △
Page 14 and 15: 4 CHAPTER 1. INTRODUCTION ¡ ¡ ¡
Page 16 and 17: 6 CHAPTER 1. INTRODUCTION and symme
Page 18 and 19: 8 CHAPTER 2. ARTIFICIAL CHEMISTRIES
Page 20 and 21: 10 CHAPTER 2. ARTIFICIAL CHEMISTRIE
Page 22: 12 CHAPTER 2. ARTIFICIAL CHEMISTRIE
Page 25 and 26: 3.1. EXTENDED HÜCKEL THEORY 15 is
Page 27 and 28: 3.2. FURTHER APPROXIMATIONS 17 K. F
Page 29 and 30: 3.2. FURTHER APPROXIMATIONS 19 Figu
Page 31 and 32: 3.2. FURTHER APPROXIMATIONS 21 are
Page 33: 3.3. CHEMICAL STRUCTURE REPRESENTAT
Page 37 and 38: 3.4. WAVE FUNCTION ANALYSIS 27 Derw
Page 39 and 40: Table 3.6: Overlap matrix for prope
Page 41 and 42: 3.5. PERFORMANCE 31 3.5 Performance
Page 43 and 44: 3.6. FRONTIER MOLECULAR ORBITAL THE
Page 45 and 46: Chapter 4 Chemical reactions A mole
Page 47 and 48: 4.1. GRAPH REWRITING 37 Graphical t
Page 49 and 50: 4.1. GRAPH REWRITING 39 C C C C C C
Page 51 and 52: 4.2. GRAPH REWRITE ENGINE 41 O O O
Page 53 and 54: Chapter 5 Reaction networks 5.1 Net
Page 55 and 56: 5.3. NETWORK PROPERTIES 45 O 3 NO 3
Page 57 and 58: 5.3. NETWORK PROPERTIES 47 (see ch.
Page 59 and 60: Chapter 6 Computational results Whe
Page 61 and 62: O O O O O O O O O O O O O O O O O O
Page 63 and 64: 6.3. GRAPH-THEORETIC PROPERTIES 53
Page 65 and 66: Chapter 7 Conclusion and Outlook Th
Page 67 and 68: Using the rules of mass action kine
Page 69 and 70: Appendix A Parameters The energy ca
Page 71 and 72: Appendix B GRW GRW is implemented i
Page 73 and 74: Appendix C Organic reactions Fromht
Page 75 and 76: Bibliography [1] R. Albert and A.-L
Page 77 and 78: BIBLIOGRAPHY 67 [25] O. Diels and K
Page 79 and 80: BIBLIOGRAPHY 69 [50] J. Gasteiger a
Page 81 and 82: BIBLIOGRAPHY 71 [76] W. Langenbeck.
Page 83 and 84: BIBLIOGRAPHY 73 [102] S. Schuster,
Page 85:
BIBLIOGRAPHY 75 [126] R. Woodward a
Page 89 and 90:
The Wooing of Archibald Modern tren
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A Toy Model of Chemical Reaction Networks - TBI - UniversitÃ¤t Wien

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