Computational Biology of Transcription Factor Binding /
| Autor Corporativo: | |
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| Otros Autores: | |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Totowa, NJ :
Humana Press : Imprint: Humana,
2010.
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| Edición: | 1st ed. 2010. |
| Colección: | Methods in Molecular Biology,
674 |
| Materias: |
Tabla de Contenidos:
- An Overview of the Computational Analyses and Discovery of Transcription Factor Binding Sites
- Components and Mechanisms of Regulation of Gene Expression
- Regulatory Regions in DNA: Promoters, Enhancers, Silencers, and Insulators
- Three-Dimensional Structures of DNA-Bound Transcriptional Regulators
- Identification of Promoter Regions and Regulatory Sites
- Motif Discovery Using Expectation Maximization and Gibbs’ Sampling
- Probabilistic Approaches to Transcription Factor Binding Site Prediction
- The Motif Tool Assessment Platform (MTAP) for Sequence-Based Transcription Factor Binding Site Prediction Tools
- Computational Analysis of ChIP-seq Data
- Probabilistic Peak Calling and Controlling False Discovery Rate Estimations in Transcription Factor Binding Site Mapping from ChIP-seq
- Sequence Analysis of Chromatin Immunoprecipitation Data for Transcription Factors
- Inferring Protein–DNA Interaction Parameters from SELEX Experiments
- Kernel-Based Identification of Regulatory Modules
- Identification of Transcription Factor Binding Sites Derived from Transposable Element Sequences Using ChIP-seq
- Target Gene Identification via Nuclear Receptor Binding Site Prediction
- Computing Chromosome Conformation
- Large-Scale Identification and Analysis of C-Proteins
- Evolution of cis-Regulatory Sequences in Drosophila
- Regulating the Regulators: Modulators of Transcription Factor Activity
- Annotating the Regulatory Genome
- Computational Identification of Plant Transcription Factors and the Construction of the PlantTFDB Database
- Practical Computational Methods for Regulatory Genomics: A cisGRN-Lexicon and cisGRN-Browser for Gene Regulatory Networks
- Reconstructing Transcriptional Regulatory Networks Using Three-Way Mutual Information and Bayesian Networks
- Computational Methods for Analyzing Dynamic Regulatory Networks.