Regulatory genomics [[electronic resource] ] : proceedings of the 3rd annual RECOMB workshop : National University of Singapore, Singapore 17-18 July 2006 / / editors, Leong Hon Wai, Sung Wing-Kin, Eleazar Eskin |
Pubbl/distr/stampa | London, : Imperial College Press, c2008 |
Descrizione fisica | 1 online resource (144 p.) |
Disciplina | 572.865 |
Altri autori (Persone) |
EskinEleazar
LeongHon Wai <1955-> SungWing-Kin |
Collana | Series on advances in bioinformatics and computational biology |
Soggetto topico |
Genetic regulation
Genomics |
Soggetto genere / forma | Electronic books. |
ISBN | 1-84816-252-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Foreword; RECOMB Regulatory Genomics 2006 Organization; CONTENTS; Keynote Papers; Computational Prediction of Regulatory Elements by Comparative Sequence Analysis M. Tompa; A Tale of Two Topics - Motif Significance and Sensitivity of Spaced Seeds M. Li; Computational Challenges for Top-Down Modeling and Simulation of Biological Pathways S. Miyano; An Improved Gibbs Sampling Method for Motif Discovery via Sequence Weighting T. Jiang; Discovering Motifs with Transcription Factor Domain Knowledge F. Chin; Applications of ILP in Computational Biology A . Dress
On the Evolution of Transcription Regulation Networks R. Shamir Systems Pharmacology in Cancer Therapeutics: Iterative Informatics-Experimental Interface E. Liu; Computational Structural Proteomics and Inhibitor Discovery R. Abagyan; Characterization of Transcriptional Responses to Environmental Stress by Differential Location Analysis H. Tang; A Knowledge-based Hybrid Algorithm for Protein Secondary Structure Prediction W. L. Hsu; Monotony and Surprise (Conservative Approaches to Pattern Discovery) A . Apostolic0; Evolution of Bacterial Regulatory Systems M. S. Gelfand; Contributed Papers TScan: A Two-step De NOVO Motif Discovery Method 0. Abul, G. K. Sandve, and F. Drabbs1. Introduction; 2. Method; 2.1. Step 1; 2.2. Step 2; 2.2.1, Over-representation Conservation Scoring; 2.2.2. Frith et al. Scoring; 3. Experiments; 4. Conclusion; References; Redundancy Elimination in Motif Discovery Algorithms H. Leung and F. Chin; 1. Introduction; 2. Maximizing Likelihood; 3. The Motif Redundancy Problem; 3.1. The motif redundancy problem; 3.2. Formal definition; 4. Algorithm; 5. Experimental Results; 6. Concluding Remarks; Appendix; References GAMOT: An Efficient Genetic Algorithm for Finding Challenging Motifs in DNA Sequences N. Karaoglu, S. Maurer-Stroh, and B. Manderick1. Introduction; 2. GA for Motif Finding; 3. An Efficient Algorithm (GAMOT); 3.1. Fast motif discovery; 3.2. The genetic algorithm; 4. Experimental Results; 4.1. Comparison with exhaustive search; 4.2. Comparison with GAI and GA2; 4.3. Comparison with other algorithms; 4.3.1. Quality of the solutions; 4.4. GAMOTparameters; 5. Conclusions and Future Work; References; Identification of Spaced Regulatory Sites via Submotif Modeling E. Wijaya and R. Kanagasabai 1. Introduction 2. Related Work; 3. Our Approach; 4. Problem Definition; 5. Algorithm SPACE; 5.1. Generation of candidate motifs; 5.2. Constrained frequent pattern mining; 5.2.1. Generalized gap; 5.2.2. Mining of constrained frequent patterns; 5.3. Significance testing and scoring; 6. Experimental Results; 6.1. Results on Tompa's benchmark data set; 6.2. Results on synthetic data set; 7. Discussion and Conclusions; References; Refining Motif Finders with E-value Calculations N. Nagarajan, P. Ng, and U. Keich; 1. Introduction; 2. Efficiently Computing E-values 3. Optimizing for E-values - Conspv |
Record Nr. | UNINA-9910455059103321 |
London, : Imperial College Press, c2008 | ||
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Lo trovi qui: Univ. Federico II | ||
|
Regulatory genomics [[electronic resource] ] : proceedings of the 3rd annual RECOMB workshop : National University of Singapore, Singapore 17-18 July 2006 / / editors, Leong Hon Wai, Sung Wing-Kin, Eleazar Eskin |
Pubbl/distr/stampa | London, : Imperial College Press, c2008 |
Descrizione fisica | 1 online resource (144 p.) |
Disciplina | 572.865 |
Altri autori (Persone) |
EskinEleazar
LeongHon Wai <1955-> SungWing-Kin |
Collana | Series on advances in bioinformatics and computational biology |
Soggetto topico |
Genetic regulation
Genomics |
ISBN | 1-84816-252-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Foreword; RECOMB Regulatory Genomics 2006 Organization; CONTENTS; Keynote Papers; Computational Prediction of Regulatory Elements by Comparative Sequence Analysis M. Tompa; A Tale of Two Topics - Motif Significance and Sensitivity of Spaced Seeds M. Li; Computational Challenges for Top-Down Modeling and Simulation of Biological Pathways S. Miyano; An Improved Gibbs Sampling Method for Motif Discovery via Sequence Weighting T. Jiang; Discovering Motifs with Transcription Factor Domain Knowledge F. Chin; Applications of ILP in Computational Biology A . Dress
On the Evolution of Transcription Regulation Networks R. Shamir Systems Pharmacology in Cancer Therapeutics: Iterative Informatics-Experimental Interface E. Liu; Computational Structural Proteomics and Inhibitor Discovery R. Abagyan; Characterization of Transcriptional Responses to Environmental Stress by Differential Location Analysis H. Tang; A Knowledge-based Hybrid Algorithm for Protein Secondary Structure Prediction W. L. Hsu; Monotony and Surprise (Conservative Approaches to Pattern Discovery) A . Apostolic0; Evolution of Bacterial Regulatory Systems M. S. Gelfand; Contributed Papers TScan: A Two-step De NOVO Motif Discovery Method 0. Abul, G. K. Sandve, and F. Drabbs1. Introduction; 2. Method; 2.1. Step 1; 2.2. Step 2; 2.2.1, Over-representation Conservation Scoring; 2.2.2. Frith et al. Scoring; 3. Experiments; 4. Conclusion; References; Redundancy Elimination in Motif Discovery Algorithms H. Leung and F. Chin; 1. Introduction; 2. Maximizing Likelihood; 3. The Motif Redundancy Problem; 3.1. The motif redundancy problem; 3.2. Formal definition; 4. Algorithm; 5. Experimental Results; 6. Concluding Remarks; Appendix; References GAMOT: An Efficient Genetic Algorithm for Finding Challenging Motifs in DNA Sequences N. Karaoglu, S. Maurer-Stroh, and B. Manderick1. Introduction; 2. GA for Motif Finding; 3. An Efficient Algorithm (GAMOT); 3.1. Fast motif discovery; 3.2. The genetic algorithm; 4. Experimental Results; 4.1. Comparison with exhaustive search; 4.2. Comparison with GAI and GA2; 4.3. Comparison with other algorithms; 4.3.1. Quality of the solutions; 4.4. GAMOTparameters; 5. Conclusions and Future Work; References; Identification of Spaced Regulatory Sites via Submotif Modeling E. Wijaya and R. Kanagasabai 1. Introduction 2. Related Work; 3. Our Approach; 4. Problem Definition; 5. Algorithm SPACE; 5.1. Generation of candidate motifs; 5.2. Constrained frequent pattern mining; 5.2.1. Generalized gap; 5.2.2. Mining of constrained frequent patterns; 5.3. Significance testing and scoring; 6. Experimental Results; 6.1. Results on Tompa's benchmark data set; 6.2. Results on synthetic data set; 7. Discussion and Conclusions; References; Refining Motif Finders with E-value Calculations N. Nagarajan, P. Ng, and U. Keich; 1. Introduction; 2. Efficiently Computing E-values 3. Optimizing for E-values - Conspv |
Record Nr. | UNINA-9910777933003321 |
London, : Imperial College Press, c2008 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Regulatory genomics : proceedings of the 3rd annual RECOMB workshop : National University of Singapore, Singapore 17-18 July 2006 / / editors, Leong Hon Wai, Sung Wing-Kin, Eleazar Eskin |
Edizione | [1st ed.] |
Pubbl/distr/stampa | London, : Imperial College Press, c2008 |
Descrizione fisica | 1 online resource (144 p.) |
Disciplina | 572.865 |
Altri autori (Persone) |
EskinEleazar
LeongHon Wai <1955-> SungWing-Kin |
Collana | Series on advances in bioinformatics and computational biology |
Soggetto topico |
Genetic regulation
Genomics |
ISBN | 1-84816-252-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Foreword; RECOMB Regulatory Genomics 2006 Organization; CONTENTS; Keynote Papers; Computational Prediction of Regulatory Elements by Comparative Sequence Analysis M. Tompa; A Tale of Two Topics - Motif Significance and Sensitivity of Spaced Seeds M. Li; Computational Challenges for Top-Down Modeling and Simulation of Biological Pathways S. Miyano; An Improved Gibbs Sampling Method for Motif Discovery via Sequence Weighting T. Jiang; Discovering Motifs with Transcription Factor Domain Knowledge F. Chin; Applications of ILP in Computational Biology A . Dress
On the Evolution of Transcription Regulation Networks R. Shamir Systems Pharmacology in Cancer Therapeutics: Iterative Informatics-Experimental Interface E. Liu; Computational Structural Proteomics and Inhibitor Discovery R. Abagyan; Characterization of Transcriptional Responses to Environmental Stress by Differential Location Analysis H. Tang; A Knowledge-based Hybrid Algorithm for Protein Secondary Structure Prediction W. L. Hsu; Monotony and Surprise (Conservative Approaches to Pattern Discovery) A . Apostolic0; Evolution of Bacterial Regulatory Systems M. S. Gelfand; Contributed Papers TScan: A Two-step De NOVO Motif Discovery Method 0. Abul, G. K. Sandve, and F. Drabbs1. Introduction; 2. Method; 2.1. Step 1; 2.2. Step 2; 2.2.1, Over-representation Conservation Scoring; 2.2.2. Frith et al. Scoring; 3. Experiments; 4. Conclusion; References; Redundancy Elimination in Motif Discovery Algorithms H. Leung and F. Chin; 1. Introduction; 2. Maximizing Likelihood; 3. The Motif Redundancy Problem; 3.1. The motif redundancy problem; 3.2. Formal definition; 4. Algorithm; 5. Experimental Results; 6. Concluding Remarks; Appendix; References GAMOT: An Efficient Genetic Algorithm for Finding Challenging Motifs in DNA Sequences N. Karaoglu, S. Maurer-Stroh, and B. Manderick1. Introduction; 2. GA for Motif Finding; 3. An Efficient Algorithm (GAMOT); 3.1. Fast motif discovery; 3.2. The genetic algorithm; 4. Experimental Results; 4.1. Comparison with exhaustive search; 4.2. Comparison with GAI and GA2; 4.3. Comparison with other algorithms; 4.3.1. Quality of the solutions; 4.4. GAMOTparameters; 5. Conclusions and Future Work; References; Identification of Spaced Regulatory Sites via Submotif Modeling E. Wijaya and R. Kanagasabai 1. Introduction 2. Related Work; 3. Our Approach; 4. Problem Definition; 5. Algorithm SPACE; 5.1. Generation of candidate motifs; 5.2. Constrained frequent pattern mining; 5.2.1. Generalized gap; 5.2.2. Mining of constrained frequent patterns; 5.3. Significance testing and scoring; 6. Experimental Results; 6.1. Results on Tompa's benchmark data set; 6.2. Results on synthetic data set; 7. Discussion and Conclusions; References; Refining Motif Finders with E-value Calculations N. Nagarajan, P. Ng, and U. Keich; 1. Introduction; 2. Efficiently Computing E-values 3. Optimizing for E-values - Conspv |
Record Nr. | UNINA-9910822091103321 |
London, : Imperial College Press, c2008 | ||
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Lo trovi qui: Univ. Federico II | ||
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