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Computational methods for understanding bacterial and archaeal genomes

Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to d...

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Други автори: Xu, Ying, 1960-, Gogarten, J. Peter.
Формат: Електронен
Език: English
Публикувано: London : Hackensack, NJ : Imperial College Press ; Distributed by World Scientific Publishing, ℗♭2008.
Серия: Series on advances in bioinformatics and computational biology ; v. 7.
Предмети:
Онлайн достъп: http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=516745
Подобни документи: Print version:: Computational methods for understanding bacterial and archaeal genomes.
Съдържание:
  • Preface; CONTENTS; List of Contributors; Acknowledgments; 1. General Characteristics of Prokaryotic Genomes Jan Mr azek and Anne O. Summers; 1. Introduction; 1.1. The Replicon Concept and Classification of Replicons; 1.2. Physical Organization of Replicons in the Cell; 2. Overall Properties of Prokaryotic Chromosomes; 2.1. Size and Gene Content; 2.2. Why Are Prokaryotic Chromosomes Small?; 2.3. G+C Content; 2.4. Oligonucleotide Composition and Genome Signature; 2.5. Amino Acid Composition and Adaptation to Growth at High Temperatures; 3. Heterogeneity of Prokaryotic Chromosomes.
  • 3.1. Intrachromosomal Variance of Nucleotide and Oligonucleotide Composition3.2. Synonymous Codon Usage; 3.3. Identification of Genomic Islands and Lateral Gene Transfer Events; 3.4. G-C Skew; 4. Repeats in Prokaryotic Genomes; 4.1. Large Repeats and Duplications; 4.2. Transposons and Insertion Sequences; 4.3. Integrons; 4.4. Chimeric Mobile Elements: Conjugative Transposons, ICEs, Plasmid-Prophages, Transposon-Prophages, Genomic Islands, and Genetic Litter; 4.5. Retrons; 4.6. Short Dispersed Repeats; 4.7. Simple Sequence Repeats; 4.8. CRISPR Repeats; 5. Further Reading; Acknowledgments.
  • 2. Genes in Prokaryotic Genomes and Their Computational Prediction Rajeev K. Azad1. Introduction; 2. Inhomogeneous Markov Models; 2.1. The GeneMark Program; 3. Interpolated Markov Models; 3.1. The Glimmer Program; 3.2. Using Deleted Interpolation in Gene Prediction; 4. Hidden Markov Models; 4.1. The Forward-Backward Algorithm; 4.2. The Viterbi Algorithm; 4.3. HMM Training; 4.4. The ECOPARSE Program; 4.5. The GeneHacker Program; 4.6. HMM Versions of the GeneMark Program; 5. Fourier Transform Methods; 5.1. The GeneScan Program; 5.2. The Lengthen-Shu.e Program; 6. Self-Organizing Maps.
  • 6.1. The RescueNet Program7. Directed Acyclic Graphs; 7.1. The FrameD Program; 8. Linear Discriminant Function; 8.1. The ZCURVE Program; 9. Unsupervised Model Training: The Self-Learning Algorithms; 9.1. The GeneMark-Genesis Program; 9.2. The GeneMarkS Program; 9.3. The MED Program; 10. Using Similarity Search in Gene Prediction; 10.1. The ORPHEUS Program; 10.2. The CRITICA Program; 10.3. The BDGF Program; 10.4. The EasyGene Program; 10.5. The GISMO Program; 11. Gene Start Prediction; 12. Resolving Overlapping Genes; 13. Non-coding RNA Gene Prediction; 14. Assessing Gene Prediction Programs.
  • 15. Discussion16. Further Reading; Acknowledgments; 3. Evolution of the Genetic Code: Computational Methods and Inferences Greg Fournier; 1. Introduction; 1.1. The Amino Acids; 1.2. Codon Designations; 1.3. Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview.