Emerging trends in computational biology, bioinformatics, and systems biology algorithms and software tools
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytical and algorithms, mathematical modeling and simulation techniques. Part I: Computatio...
| Otros Autores: | , , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Amsterdam, [Netherlands] :
Morgan Kaufmann
2015.
|
| Edición: | First edition |
| Colección: | Emerging Trends in Computer Science and Applied Computing
|
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629706906719 |
Tabla de Contenidos:
- Front Cover; Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology: Algorithms and Software Tools; Copyright; Contents; Contributors; Preface; Acknowledgments; Introduction; Chapter 1: Supervised Learning with the Artificial Neural Networks Algorithm for Modeling Immune Cell Differentiation; 1. Introduction; 1.A. Immune cell differentiation and modeling; 1.B. MSM and model reduction; 1.C. ANN algorithm and its applications; 2. Related work; 3. Modeling immune cell differentiation; 3.1. T cell differentiation process as a use case
- 3.2. Data for training and testing models3.3. ANN model; 3.4. Comparative analysis with the LR model and SVM; 3.5. Capability of ANN model to analyze data with noise; 4. Discussion; 5. Conclusion; References; References; Chapter 2: Accelerating Techniques for Particle Filter Implementations on FPGA; 1. Introduction; 2. PF and SLAM algorithms; 2.1. Particle filtering; 2.2. Application of PF to SLAM; 3. Computational bottleneck identification and hardware/software partitioning; 4. PF acceleration techniques; 4.1. CORDIC acceleration technique; 4.2. Ziggurat acceleration technique
- 5. Hardware implementation6. Hardware/software Architecture; 7. Results and discussion; 8. Conclusions; References; Chapter 3: Biological Study on Pulsatile Flow of Herschel-Bulkley Fluid in Tapered Blood Vessels; 1. Introduction; 2. Formulation of the problem; 3. Solution; 4. Discussion; 5. Conclusion; References; Chapter 4: Hierarchical k-Means: A Hybrid Clustering Algorithm and Its Application to Study Gene Expression in Lung Adeno ...; 1. Introduction; 2. Methods; 3. Data Set; 4. Results and Discussion; 5. Conclusions; References; Supplementary Materials
- Chapter 5: Molecular Classification of N-Aryloxazolidinone-5-carboxamides as Human Immunodeficiency Virus Protease Inhibitors1. Introduction; 2. Computational method; 3. Classification algorithm; 4. Information entropy; 5. The EC of entropy production; 6. Learning procedure; 7. Calculation results and discussion; 8. Conclusions; Acknowledgment; References; Chapter 6: Review of Recent Protein-Protein Interaction Techniques; 1. Introduction; 2. Technical challenges and open issues; 3. Performance measures; 4. Computational approaches; 4.1. Sequence-based approaches
- 4.1.1. Statistical sequence-based approaches4.1.1.1. Mirror tree method; 4.1.1.2. PIPE; 4.1.1.3. CD; 4.1.2. ML sequence-based approaches; 4.1.2.1. Auto covariance; 4.1.2.2. Pairwise similarity; 4.1.2.3. AA composition; 4.1.2.4. AA Triad; 4.1.2.5. UNISPPI; 4.1.2.6. ETB-Viterbi; 4.2. Structure-based approaches; 4.2.1. Template structure-based approaches; 4.2.1.1. PRISM; 4.2.1.2. PrePPI; 4.2.2. Statistical structure-based approaches; 4.2.2.1. PID matrix score; 4.2.2.2. PreSPI; 4.2.2.3. DCC; 4.2.2.4. MEGADOCK; 4.2.2.5. Meta approach; 4.2.3. ML structure-based approaches; 4.2.3.1. Random Forest
- 4.2.3.2. Struct2Net
