Analysis of Microarray Data: A Network-Based Approach
Book information
Description
This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: Understanding and Preprocessing Microarray Data Clustering of Microarray Data Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order Bilayer Verification Algorithm Probabilistic Boolean Networks as Models for Gene Regulation Estimating Transcriptional Regulatory Networks by a Bayesian Network Analysis of Therapeutic Compound Effects Statistical Methods for Inference of Genetic Networks and Regulatory Modules Identification of Genetic Networks by Structural Equations Predicting Functional Modules Using Microarray and Protein Interaction Data Integrating Results from Literature Mining and Microarray Experiments to Infer Gene Networks The book is for both, scientists using the technique as well as those developing new analysis techniques.
Similar books
Elements of Data Science, Machine Learning, and Artificial Intelligence Using R
2023 · PDF
Mathematical Foundations of Data Science Using R
2022 · EPUB
Mathematical Foundations of Data Science Using R
2020 · EPUB
Frontiers In Data Science
2018 · PDF
Mathematical Foundations of Data Science Using R
2020 · PDF
Frontiers in Data Science
2018 · PDF
Big Data of Complex Networks
2016 · PDF
Mathematical Foundations and Applications of Graph Entropy
2016 · PDF