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Preface; Acknowledgments; Contents; Image Segmentation, Processing and Analysis in Microscopy and Life Science; 1 Pixels and Color Channels; 2 Image Segmentation; 2.1 Thresholding; 2.2 Watershed Segmentation; 2.3 Shape-Based Watershed Segmentation; 2.4 Edge-Based Watershed Segmentation; 2.5 Merging; 2.6 Seeded Watershed Segmentation; 2.7 Extension to Volume Images and Time-Lapse Experiments; 2.8 Other Segmentation Methods; 3 Feature Extraction and Classification in Large-Scale Image Based Biomedical Screening; References
Image Analysis and Classification for High-Throughput Screening of Embryonic Stem Cells1 Introduction; 2 Software System Components; 2.1 Pre-Processing; 2.2 Segmentation; 2.3 Features Computation; 2.4 Classification; 3 Experimental Results; 3.1 Performance Metrics; 3.2 Evaluation of the Segmentation Step; 3.3 First Classification Results; 4 Concluding Remarks; References; Exploiting ``Mental'' Images in Artificial NeuralNetwork Computation; 1 Introduction; 2 DRASiW Model; 3 Mental Images; 4 Improving DRASiW Performance; 4.1 Tracking Deformable Objects; 4.2 Generating Background Models
4.3 Improving Classification5 Conclusions; References; Applying Design of Experiments Methodology to PEI Toxicity Assay on Neural Progenitor Cells; 1 Design of Experiments as a Method for Protocol Optimization; 2 Main Aspects of DoE Methodology; 3 DoE Applications from Industry to Biological Research; 4 Our Case Study: The Set-Up and Optimisation of a Transfection Protocol for Neural Progenitor Cells; 5 DoE Methodology Applied to Toxicity Assay; 5.1 Factorial Designs and Residual Analysis; 5.2 Factors and Interactions Significance Analysis; 5.3 Model Refining and Validation; 6 Conclusions
2 MiRNA Transcriptional Regulation2.1 Challenges of in silico miRNA Promoter Identification; 2.2 Next Generation Sequencing (NGS) Technology Leads to Significant Advances in miRNA Promoter Prediction; 2.3 Classification and Comparison of miRNA Promoter Prediction Methods; 2.3.1 miRNA-Mediated Regulatory Network Reconstruction; 3 Predictive Models of miRNA Processing; 4 Conclusions; References; Tunicate Neurogenesis: The Case of the SoxB2 Missing CNE; 1 Introduction; 2 Results; 3 Discussion; 4 Materials and Methods; 4.1 Animals and Embryos; 4.2 Comparative Genomics
Image Analysis and Classification for High-Throughput Screening of Embryonic Stem Cells1 Introduction; 2 Software System Components; 2.1 Pre-Processing; 2.2 Segmentation; 2.3 Features Computation; 2.4 Classification; 3 Experimental Results; 3.1 Performance Metrics; 3.2 Evaluation of the Segmentation Step; 3.3 First Classification Results; 4 Concluding Remarks; References; Exploiting ``Mental'' Images in Artificial NeuralNetwork Computation; 1 Introduction; 2 DRASiW Model; 3 Mental Images; 4 Improving DRASiW Performance; 4.1 Tracking Deformable Objects; 4.2 Generating Background Models
4.3 Improving Classification5 Conclusions; References; Applying Design of Experiments Methodology to PEI Toxicity Assay on Neural Progenitor Cells; 1 Design of Experiments as a Method for Protocol Optimization; 2 Main Aspects of DoE Methodology; 3 DoE Applications from Industry to Biological Research; 4 Our Case Study: The Set-Up and Optimisation of a Transfection Protocol for Neural Progenitor Cells; 5 DoE Methodology Applied to Toxicity Assay; 5.1 Factorial Designs and Residual Analysis; 5.2 Factors and Interactions Significance Analysis; 5.3 Model Refining and Validation; 6 Conclusions
2 MiRNA Transcriptional Regulation2.1 Challenges of in silico miRNA Promoter Identification; 2.2 Next Generation Sequencing (NGS) Technology Leads to Significant Advances in miRNA Promoter Prediction; 2.3 Classification and Comparison of miRNA Promoter Prediction Methods; 2.3.1 miRNA-Mediated Regulatory Network Reconstruction; 3 Predictive Models of miRNA Processing; 4 Conclusions; References; Tunicate Neurogenesis: The Case of the SoxB2 Missing CNE; 1 Introduction; 2 Results; 3 Discussion; 4 Materials and Methods; 4.1 Animals and Embryos; 4.2 Comparative Genomics