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Bioinformatics [[electronic resource] ] : genomics and post-genomics / / Frédéric Dardel and François Képès ; translated by Noah Hardy
| Bioinformatics [[electronic resource] ] : genomics and post-genomics / / Frédéric Dardel and François Képès ; translated by Noah Hardy |
| Autore | Dardel Frédéric |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 |
| Descrizione fisica | 1 online resource (253 p.) |
| Disciplina |
570.285
572.80285 |
| Altri autori (Persone) | KépèsFrançois |
| Soggetto topico |
Bioinformatics
Genomics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-73873-1
9786610738731 0-470-02003-2 0-470-02002-4 |
| Classificazione |
BIO 110f
BIO 180f WC 7700 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface to the French edition; Preface to the English edition; 1: Genome sequencing; 1.1 Automatic sequencing; 1.2 Sequencing strategies; 1.3 Fragmentation strategies; 1.4 Sequence assembly; 1.5 Filling gaps; 1.6 Obstacles to reconstruction; 1.7 Utilizing a complementary 'large'1 clone library; 1.8 The first large-scale sequencing project: The Haemophilus influenzae genome; 1.9 cDNA and EST; 2: Sequence comparisons; 2.1 Introduction: Comparison as a sequence prediction method; 2.2 A sample molecule: the human androsterone receptor
2.3 Sequence homologies - functional homologies2.4 Comparison matrices; 2.5 The problem of insertions and deletions; 2.6 Optimal alignment: the dynamic programming method; 2.7 Fast heuristic methods; 2.8 Sensitivity, specificity, and confidence level; 2.9 Multiple alignments; 3: Comparative genomics; 3.1 General properties of genomes; 3.2 Genome comparisons; 3.3 Gene evolution and phylogeny: applications to annotation; 4: Genetic information and biological sequences; 4.1 Introduction: Coding levels; 4.2 Genes and the genetic code; 4.3 Expression signals; 4.4 Specific sites 4.5 Sites located on DNA4.6 Sites present on RNA; 4.7 Pattern detection methods; 5: Statistics and sequences; 5.1 Introduction; 5.2 Nucleotide base and amino acid distribution; 5.3 The biological basis of codon bias; 5.4 Using statistical bias for prediction; 5.5 Modeling DNA sequences; 5.6 Complex models; 5.7 Sequencing errors and hidden Markov models; 5.8 Hidden Markov processes: a general sequence analysis tool; 5.9 The search for genes - a difficult art; 6: Structure prediction; 6.1 The structure of RNA; 6.2 Properties of the RNA molecule; 6.3 Secondary RNA structures 6.4 Thermodynamic stability of RNA structures6.5 Finding the most stable structure; 6.6 Validation of predicted secondary structures; 6.7 Using chemical and enzymatic probing to analyze folding; 6.8 Long-distance interactions and three-dimensional structure prediction; 6.9 Protein structure; 6.10 Secondary structure prediction; 6.11 Three-dimensional modeling based on homologous protein structure; 6.12 Predicting folding; 7: Transcriptome and proteome: macromolecular networks; 7.1 Introduction; 7.2 Post-genomic methods; 7.3 Macromolecular networks; 7.4 Topology of macromolecular networks 7.5 Modularity and dynamics of macromolecular networks7.6 Inference of regulatory networks; 8: Simulation of biological processes in the genome context; 8.1 Types of simulations; 8.2 Prediction and explanation; 8.3 Simulation of molecular networks; 8.4 Generic post-genomic simulators; Index |
| Record Nr. | UNINA-9910143739203321 |
Dardel Frédéric
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Bioinformatics [[electronic resource] ] : genomics and post-genomics / / Frédéric Dardel and François Képès ; translated by Noah Hardy
| Bioinformatics [[electronic resource] ] : genomics and post-genomics / / Frédéric Dardel and François Képès ; translated by Noah Hardy |
| Autore | Dardel Frédéric |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 |
| Descrizione fisica | 1 online resource (253 p.) |
| Disciplina |
570.285
572.80285 |
| Altri autori (Persone) | KépèsFrançois |
| Soggetto topico |
Bioinformatics
Genomics |
| ISBN |
1-280-73873-1
9786610738731 0-470-02003-2 0-470-02002-4 |
| Classificazione |
BIO 110f
BIO 180f WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface to the French edition; Preface to the English edition; 1: Genome sequencing; 1.1 Automatic sequencing; 1.2 Sequencing strategies; 1.3 Fragmentation strategies; 1.4 Sequence assembly; 1.5 Filling gaps; 1.6 Obstacles to reconstruction; 1.7 Utilizing a complementary 'large'1 clone library; 1.8 The first large-scale sequencing project: The Haemophilus influenzae genome; 1.9 cDNA and EST; 2: Sequence comparisons; 2.1 Introduction: Comparison as a sequence prediction method; 2.2 A sample molecule: the human androsterone receptor
2.3 Sequence homologies - functional homologies2.4 Comparison matrices; 2.5 The problem of insertions and deletions; 2.6 Optimal alignment: the dynamic programming method; 2.7 Fast heuristic methods; 2.8 Sensitivity, specificity, and confidence level; 2.9 Multiple alignments; 3: Comparative genomics; 3.1 General properties of genomes; 3.2 Genome comparisons; 3.3 Gene evolution and phylogeny: applications to annotation; 4: Genetic information and biological sequences; 4.1 Introduction: Coding levels; 4.2 Genes and the genetic code; 4.3 Expression signals; 4.4 Specific sites 4.5 Sites located on DNA4.6 Sites present on RNA; 4.7 Pattern detection methods; 5: Statistics and sequences; 5.1 Introduction; 5.2 Nucleotide base and amino acid distribution; 5.3 The biological basis of codon bias; 5.4 Using statistical bias for prediction; 5.5 Modeling DNA sequences; 5.6 Complex models; 5.7 Sequencing errors and hidden Markov models; 5.8 Hidden Markov processes: a general sequence analysis tool; 5.9 The search for genes - a difficult art; 6: Structure prediction; 6.1 The structure of RNA; 6.2 Properties of the RNA molecule; 6.3 Secondary RNA structures 6.4 Thermodynamic stability of RNA structures6.5 Finding the most stable structure; 6.6 Validation of predicted secondary structures; 6.7 Using chemical and enzymatic probing to analyze folding; 6.8 Long-distance interactions and three-dimensional structure prediction; 6.9 Protein structure; 6.10 Secondary structure prediction; 6.11 Three-dimensional modeling based on homologous protein structure; 6.12 Predicting folding; 7: Transcriptome and proteome: macromolecular networks; 7.1 Introduction; 7.2 Post-genomic methods; 7.3 Macromolecular networks; 7.4 Topology of macromolecular networks 7.5 Modularity and dynamics of macromolecular networks7.6 Inference of regulatory networks; 8: Simulation of biological processes in the genome context; 8.1 Types of simulations; 8.2 Prediction and explanation; 8.3 Simulation of molecular networks; 8.4 Generic post-genomic simulators; Index |
| Record Nr. | UNINA-9910831026903321 |
|
Dardel Frédéric
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Bioinformatics : genomics and post-genomics / / Frederic Dardel and Francois Kepes ; translated by Noah Hardy
| Bioinformatics : genomics and post-genomics / / Frederic Dardel and Francois Kepes ; translated by Noah Hardy |
| Autore | Dardel Frédéric |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 |
| Descrizione fisica | 1 online resource (253 p.) |
| Disciplina |
570.285
572.80285 |
| Altri autori (Persone) | KépèsFrançois |
| Soggetto topico |
Bioinformatics
Genomics |
| ISBN |
9786610738731
9781280738739 1280738731 9780470020036 0470020032 9780470020029 0470020024 |
| Classificazione |
BIO 110f
BIO 180f WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface to the French edition; Preface to the English edition; 1: Genome sequencing; 1.1 Automatic sequencing; 1.2 Sequencing strategies; 1.3 Fragmentation strategies; 1.4 Sequence assembly; 1.5 Filling gaps; 1.6 Obstacles to reconstruction; 1.7 Utilizing a complementary 'large'1 clone library; 1.8 The first large-scale sequencing project: The Haemophilus influenzae genome; 1.9 cDNA and EST; 2: Sequence comparisons; 2.1 Introduction: Comparison as a sequence prediction method; 2.2 A sample molecule: the human androsterone receptor
2.3 Sequence homologies - functional homologies2.4 Comparison matrices; 2.5 The problem of insertions and deletions; 2.6 Optimal alignment: the dynamic programming method; 2.7 Fast heuristic methods; 2.8 Sensitivity, specificity, and confidence level; 2.9 Multiple alignments; 3: Comparative genomics; 3.1 General properties of genomes; 3.2 Genome comparisons; 3.3 Gene evolution and phylogeny: applications to annotation; 4: Genetic information and biological sequences; 4.1 Introduction: Coding levels; 4.2 Genes and the genetic code; 4.3 Expression signals; 4.4 Specific sites 4.5 Sites located on DNA4.6 Sites present on RNA; 4.7 Pattern detection methods; 5: Statistics and sequences; 5.1 Introduction; 5.2 Nucleotide base and amino acid distribution; 5.3 The biological basis of codon bias; 5.4 Using statistical bias for prediction; 5.5 Modeling DNA sequences; 5.6 Complex models; 5.7 Sequencing errors and hidden Markov models; 5.8 Hidden Markov processes: a general sequence analysis tool; 5.9 The search for genes - a difficult art; 6: Structure prediction; 6.1 The structure of RNA; 6.2 Properties of the RNA molecule; 6.3 Secondary RNA structures 6.4 Thermodynamic stability of RNA structures6.5 Finding the most stable structure; 6.6 Validation of predicted secondary structures; 6.7 Using chemical and enzymatic probing to analyze folding; 6.8 Long-distance interactions and three-dimensional structure prediction; 6.9 Protein structure; 6.10 Secondary structure prediction; 6.11 Three-dimensional modeling based on homologous protein structure; 6.12 Predicting folding; 7: Transcriptome and proteome: macromolecular networks; 7.1 Introduction; 7.2 Post-genomic methods; 7.3 Macromolecular networks; 7.4 Topology of macromolecular networks 7.5 Modularity and dynamics of macromolecular networks7.6 Inference of regulatory networks; 8: Simulation of biological processes in the genome context; 8.1 Types of simulations; 8.2 Prediction and explanation; 8.3 Simulation of molecular networks; 8.4 Generic post-genomic simulators; Index |
| Record Nr. | UNINA-9911020348503321 |
|
Dardel Frédéric
|
||
| Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics [[electronic resource] ] : 8th European Conference, EvoBIO 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings / / edited by Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini
| Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics [[electronic resource] ] : 8th European Conference, EvoBIO 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings / / edited by Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (XII, 249 p. 63 illus.) |
| Disciplina | 006.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Bioinformatics
Algorithms Database management Artificial intelligence Computer science Artificial intelligence—Data processing Computational and Systems Biology Database Management Artificial Intelligence Theory of Computation Data Science |
| ISBN |
1-280-38605-3
9786613563972 3-642-12211-6 |
| Classificazione |
BIO 110f
DAT 708f MAT 919f SS 4800 WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Variable Genetic Operator Search for the Molecular Docking Problem -- Variable Genetic Operator Search for the Molecular Docking Problem -- Role of Centrality in Network-Based Prioritization of Disease Genes -- Parallel Multi-Objective Approaches for Inferring Phylogenies -- An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Prediction -- Finding Gapped Motifs by a Novel Evolutionary Algorithm -- Top-Down Induction of Phylogenetic Trees -- A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships -- Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci -- Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions -- Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques -- Correlation–Based Scatter Search for Discovering Biclusters from Gene Expression Data -- A Local Search Appproach for Transmembrane Segment and Signal Peptide Discrimination -- A Replica Exchange Monte Carlo Algorithm for the Optimization of Secondary Structure Packing in Proteins -- Improving Multi-Relief for Detecting Specificity Residues from Multiple Sequence Alignments -- Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models -- Posters -- The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics -- Artificial Immune Systems for Epistasis Analysis in Human Genetics -- Metaheuristics for Strain Optimization Using Transcriptional Information Enriched Metabolic Models -- Using Rotation Forest for Protein Fold Prediction Problem: An Empirical Study -- Towards Automatic Detecting of Overlapping Genes - Clustered BLAST Analysis of Viral Genomes -- Investigating Populational Evolutionary Algorithms to Add Vertical Meaning in Phylogenetic Trees. |
| Record Nr. | UNISA-996465893203316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics : 8th European Conference, EvoBIO 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings / / edited by Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini
| Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics : 8th European Conference, EvoBIO 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings / / edited by Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (XII, 249 p. 63 illus.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PizzutiClara
RitchieMarylyn DeRiggi GiacobiniMario |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Bioinformatics
Algorithms Database management Artificial intelligence Computer science Artificial intelligence - Data processing Computational and Systems Biology Database Management Artificial Intelligence Theory of Computation Data Science |
| ISBN |
1-280-38605-3
9786613563972 3-642-12211-6 |
| Classificazione |
BIO 110f
DAT 708f MAT 919f SS 4800 WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Variable Genetic Operator Search for the Molecular Docking Problem -- Variable Genetic Operator Search for the Molecular Docking Problem -- Role of Centrality in Network-Based Prioritization of Disease Genes -- Parallel Multi-Objective Approaches for Inferring Phylogenies -- An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Prediction -- Finding Gapped Motifs by a Novel Evolutionary Algorithm -- Top-Down Induction of Phylogenetic Trees -- A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships -- Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci -- Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions -- Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques -- Correlation–Based Scatter Search for Discovering Biclusters from Gene Expression Data -- A Local Search Appproach for Transmembrane Segment and Signal Peptide Discrimination -- A Replica Exchange Monte Carlo Algorithm for the Optimization of Secondary Structure Packing in Proteins -- Improving Multi-Relief for Detecting Specificity Residues from Multiple Sequence Alignments -- Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models -- Posters -- The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics -- Artificial Immune Systems for Epistasis Analysis in Human Genetics -- Metaheuristics for Strain Optimization Using Transcriptional Information Enriched Metabolic Models -- Using Rotation Forest for Protein Fold Prediction Problem: An Empirical Study -- Towards Automatic Detecting ofOverlapping Genes - Clustered BLAST Analysis of Viral Genomes -- Investigating Populational Evolutionary Algorithms to Add Vertical Meaning in Phylogenetic Trees. |
| Record Nr. | UNINA-9910768441203321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Functional and Phylogenetic Ecology in R / / by Nathan G. Swenson
| Functional and Phylogenetic Ecology in R / / by Nathan G. Swenson |
| Autore | Swenson Nathan G. |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (217 p.) |
| Disciplina | 577.0285 |
| Collana | Use R! |
| Soggetto topico |
Statistics
Ecology Evolution (Biology) R (Computer program language) Statistics and Computing/Statistics Programs Evolutionary Biology |
| ISBN | 1-4614-9542-3 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Introduction -- Phylogenetic Data in R -- Phylogenetic Diversity -- Functional Diversity -- Phylogenetic & Functional Beta Diversity -- Null Models -- Comparative Methods & Phylogenetic Signal -- Partitioning the Phylogenetic, Functional, Environmental and Spatial Components of Community Diversity -- Integrating R with Other Phylogenetic and Functional Trait Analytical Software -- References -- Index. |
| Record Nr. | UNINA-9910300149403321 |
|
Swenson Nathan G.
|
||
| New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910460442103321 |
|
Wan Shibiao
|
||
| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto non controllato |
Bioinformatics
Computer Science Proteomics |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910797139603321 |
|
Wan Shibiao
|
||
| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto non controllato |
Bioinformatics
Computer Science Proteomics |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910819391103321 |
|
Wan Shibiao
|
||
| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
