Cargando…
Pathway modeling and algorithm research /
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Nova Science Publishers, Inc.,
[2011]
|
| Colección: | Computer science, technology and applications.
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- PATHWAY MODELING AND ALGORITHM RESEARCH; PATHWAY MODELING AND ALGORITHM RESEARCH; Contents; Preface; Biological Pathways and Their Modeling; Abstract; 1. Introduction; 2. Classification; 2.1. Gene Regulatory Networks (GRN); 2.2. Signaling Pathways (SP); 2.3. Metabolic Pathways (MP); 3. Modeling Biological Pathways; 4. Current Research; Conclusions; References; Supervised Learning Approaches in Pathway Modeling; Abstract; 1. Introduction; 2. Classification via Supervised Learning; 2.1. Various Approaches; 2.1.1. Artificial Neural Networks (ANN).
- 2.1.1.1. Application to Metabolic Pathway Modeling2.1.1.2. Application to Signal Transduction Modeling; 2.1.1.3. Application to Gene Regulatory Network Modeling; 2.1.2. Support Vector Machines (SVM); 2.1.2.1. Application to Metabolic Pathway Modeling; 2.1.2.2. Application to Gene Regulatory Network Modeling; 2.1.2.3. Application to Signal Transduction Modeling; 2.1.3. Nearest Neighbor Approach; 2.1.3.1. Application to Metabolic Pathway Modeling; 2.1.3.2. Application to Gene Regulatory Network Modeling; 2.1.3.3. Application to Signal Transduction Modeling; 2.1.4. Bayesian Classifier.
- 2.1.4.1. Application to Metabolic Pathway Modeling2.1.4.2. Application to Gene Regulatory Network Modeling; 2.1.4.3. Application to Signal Transduction Modeling; 2.1.5. Logistic Regression; 2.1.5.1. Application to Metabolic Pathway Modeling; 2.1.5.2. Application to Gene Regulatory Network Modeling; 2.1.5.3. Application to Signal Transduction Modeling; 2.1.6. Discriminant Analysis; 2.1.6.1. Application to Metabolic Pathway Modeling; 2.1.6.2. Application to Gene Regulatory Network Modeling; 2.1.6.3. Application to Signal Transduction Modeling; 2.1.7. Decision Trees.
- 2.1.7.1. Application to Metabolic Pathway Modeling2.1.7.2. Application to Gene Regulatory Network Modeling; 2.1.7.3. Application to Signal Transduction Modeling; 3. Current Research; Conclusions; References; Shortest Path Algorithms in Pathway Analysis; Abstract; 1. Introduction; 2. Shortest Path Algorithms; 3. Types of Shortest Path Algorithms; 3.1. Dijkstra's Algorithm; 3.1.1. Algorithm; 3.1.2. Pseudocode; 3.1.3. Time Complexity; 3.2. Bellman-Ford Algorithm; 3.2.1. Algorithm; 3.2.2. Pseudocode; 3.2.3. Time Complexity; 3.3. Floyd-Warshall algorithm; 3.3.1. Algorithm; 3.3.2. Pseudocode.
- 3.3.3. Time Complexity3.4. Johnson's Algorithm; 3.4.1. Algorithm; 3.4.2. Pseudocode; 3.4.3. Time Complexity; 3.5. Breadth First Search (BFS); 3.5.1. Algorithm; 3.5.2. Pseudocode; 3.5.3. Time Complexity; 3.6. k-Shortest Paths; 3.6.1. Algorithm; 3.6.2. Pseudo-Code; 3.6.2.1. Removing Path Algorithm; 3.6.2.2. Deviation Path Algorithm; 3.6.3. Time Complexity; 3.7. Linear Programming; 3.7.1. Algorithm; 3.7.2. Pseudo-Code; 3.7.3. Time Complexity; 4. Application of Shortest Path Algorithms in; Biological Pathways; 4.1. Application to Metabolic Pathway Modeling.