Computational and Statistical Approaches to Genomics
Computational and Statistical Genomics aims to help researchers deal with current genomic challenges. Topics covered include: overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for mi...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Boston, MA :
Springer US,
2002.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Microarray Image Analysis and Gene Expression Ratio Statistics
- Statistical Considerations in the Assessment of cDNA Microarray Data Obtained Using Amplification
- Sources of Variation in Microarray Experiments
- Studentizing Microarray Data
- Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains
- Selecting Informative Genes for Cancer Classification Using Gene Expression Data
- Design Issues and Comparison of Methods for Microarray-Based Classification
- Analyzing Protein Sequences Using Signal Analysis Techniques
- Statistics of the Numbers of Transcripts and Protein Sequences Encoded in the Genome
- Normalized Maximum Likelihood Models for Boolean Regression with Application to Prediction and Classification in Genomics
- Inference of Genetic Regulatory Networks Via Best-Fit Extensions
- Regularization and Noise Injection for Improving Genetic Network Models
- Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene Expression Relations
- Human Glioma Diagnosis from Gene Expression Data
- Application of DNA Microarray Technology to Clinical Biopsies of Breast Cancer
- Alternative Splicing: Genetic Complexity in Cancer
- Single-Nucleotide Polymorphisms, DNA Repair, and Cancer.
