Emerging trends in computational biology, bioinformatics, and systems biology : (Record no. 216339)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 06536cam a2200577 i 4500 |
040 ## - CATALOGING SOURCE | |
Transcribing agency | N$T |
019 ## - | |
-- | 919515530 |
-- | 924055503 |
-- | 956678784 |
-- | 988654386 |
-- | 1008960047 |
-- | 1066407451 |
-- | 1103260161 |
-- | 1105189868 |
-- | 1105564688 |
-- | 1129347079 |
-- | 1152981639 |
-- | 1192336832 |
-- | 1235828142 |
-- | 1240535289 |
-- | 1262690376 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9780128026465 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 0128026464 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 0128025085 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9780128025086 |
245 00 - TITLE STATEMENT | |
Title | Emerging trends in computational biology, bioinformatics, and systems biology : |
Sub title | algorithms and software tools / |
Statement of responsibility, etc. | edited by Quoc Nam Tran, Hamid Arabnia. |
300 ## - DESCRIPTION | |
Extent | 1 online resource. |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
505 8# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
505 8# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
505 8# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
505 8# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
650 #0 - SUBJECT | |
Keyword | Computational biology. |
650 #0 - SUBJECT | |
Keyword | Bioinformatics. |
650 #0 - SUBJECT | |
Keyword | Systems biology. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Tran, Quoc-Nam, |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Arabnia, Hamid, |
856 40 - ONLINE RESOURCES | |
url | http://www.sciencedirect.com/science/book/9780128025086 |
758 ## - | |
-- | has work: |
-- | Emerging trends in computational biology, bioinformatics, and systems biology (Text) |
-- | https://id.oclc.org/worldcat/entity/E39PCGkXtjfQxPqcdYwVdfHGf3 |
-- | https://id.oclc.org/worldcat/ontology/hasWork |
No items available.