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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 | ||
| ||
