Computational Systems Biology
| Institution som forfatter: | |
|---|---|
| Andre forfattere: | , , , , |
| Summary: | XVIII, 587 p. 130 illus., 3 illus. in color. text |
| Sprog: | engelsk |
| Udgivet: |
Totowa, NJ :
Humana Press : Imprint: Humana,
2009.
|
| Udgivelse: | 1st ed. 2009. |
| Serier: | Methods in Molecular Biology,
541 |
| Fag: | |
| Online adgang: | https://doi.org/10.1007/978-1-59745-243-4 |
| Format: | Electronisk Bog |
Indholdsfortegnelse:
- Network Components
- Identification of cis-Regulatory Elements in Gene Co-expression Networks Using A-GLAM
- Structure-Based Ab Initio Prediction of Transcription Factor–Binding Sites
- Inferring Protein–Protein Interactions from Multiple Protein Domain Combinations
- Prediction of Protein–Protein Interactions: A Study of the Co-evolution Model
- Computational Reconstruction of Protein–Protein Interaction Networks: Algorithms and Issues
- Prediction and Integration of Regulatory and Protein–Protein Interactions
- Detecting Hierarchical Modularity in Biological Networks
- Network Inference
- Methods to Reconstruct and Compare Transcriptional Regulatory Networks
- Learning Global Models of Transcriptional Regulatory Networks from Data
- Inferring Molecular Interactions Pathways from eQTL Data
- Methods for the Inference of Biological Pathways and Networks
- Network Dynamics
- Exploring Pathways from Gene Co-expression to Network Dynamics
- Network Dynamics
- Kinetic Modeling of Biological Systems
- Guidance for Data Collection and Computational Modelling of Regulatory Networks
- Function and Evolutionary Systems Biology
- A Maximum Likelihood Method for Reconstruction of the Evolution of Eukaryotic Gene Structure
- Enzyme Function Prediction with Interpretable Models
- Using Evolutionary Information to Find Specificity-Determining and Co-evolving Residues
- Connecting Protein Interaction Data, Mutations, and Disease Using Bioinformatics
- Effects of Functional Bias on Supervised Learning of a Gene Network Model
- Computational Infrastructure for Systems Biology
- Comparing Algorithms for Clustering of Expression Data: How to Assess Gene Clusters
- The Bioverse API and Web Application
- Computational Representation of Biological Systems
- Biological NetworkInference and Analysis Using SEBINI and CABIN.