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Advances in Bioinformatics 1st Edition by Miguel Rocha, Florentino Fernandez Riverola, Hagit Shatkay, Juan Manuel Corchado ISBN 9783642132148 3642132146

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Advances in Bioinformatics Miguel P. Rocha Digital Instant Download

Author(s): Miguel P. Rocha, Florentino Fernández Riverola, Hagit Shatkay, Juan Manuel Corchado Rodríguez
ISBN(s): 9783642132131, 3642132138
Edition: Kindle
File Details: PDF, 3.61 MB
Year: 2010
Language: english
SKU: EB-1988766 Category: Tags: , , ,

Advances in Bioinformatics 1st Edition by Miguel Rocha, Florentino Fernandez Riverola, Hagit Shatkay, Juan Manuel Corchado – Ebook PDF Instant Download/Delivery: 9783642132148 ,3642132146
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Product details:
ISBN 10: 3642132146
ISBN 13: 9783642132148
Author: Miguel Rocha, Florentino Fernandez Riverola, Hagit Shatkay, Juan Manuel Corchado

The fields of Bioinformatics and Computational Biology have been growing steadily over the last few years boosted by an increasing need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology. This calls for new algorithms and – proaches from fields such as Data Integration, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also, new global approaches, such as Systems Biology, have been emerging replacing the reductionist view that dominated biological research in the last d- ades. Indeed, Biology is more and more a science of information needing tools from the information technology field. The interaction of researchers from diff- ent scientific fields is, more than ever, of foremost importance and we hope this event will contribute to this effort. IWPACBB’10 technical program included a total of 30 papers (26 long papers and 4 short papers) spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the technical program of the conference will certainly be diverse, challenging and will promote the interaction among computer scientists, mathematicians, biologists and other researchers. We would like to thank all the contributing authors, as well as the members of the Program Committee and the Organizing Committee for their hard and highly valuable work. Their work has helped to contribute to the success of the IWAPCBB’10 event. IWPACBB’10 wouldn’t exist without your contribution.
 

Advances in Bioinformatics 1st Edition Table of contents:

  1. Microarrays
  2. Highlighting Differential Gene Expression between Two Condition Microarrays through Heterogeneous Ge
  3. Introduction
  4. Methodology
  5. Data Base Construction of Microarray and Genomic Data
  6. Kernel Construction
  7. Detection of Differences between Amastigote and Promastigote Gene Expression
  8. Results and Discussion
  9. Conclusions and Future Work
  10. References
  11. An Experimental Evaluation of a Novel Stochastic Method for Iterative Class Discovery on Real Microa
  12. Introduction
  13. Overview of the Iterative Class Discovery Algorithm
  14. Experimental Results
  15. The HC-Salamanca Dataset
  16. The Armstrong Dataset
  17. Discussion
  18. Conclusion
  19. References
  20. Automatic Workflow during the Reuse Phase of a CBP System Applied to Microarray Analysis
  21. Introduction
  22. Self-Adaptive Multiagent System for Expression Analysis
  23. Coordinator CBP-BDI Agent
  24. Results and Conclusions
  25. References
  26. A Comparative Study of Microarray Data Classification Methods Based on Ensemble Biological Relevant
  27. Introduction and Motivation
  28. Related Work
  29. Comparative Study
  30. Datasets and Base Classifiers
  31. Biological Knowledge Gene Sets
  32. Ensemble Alternatives
  33. Experimental Results and Discussion
  34. References
  35. Data Mining and Data Integration
  36. Predicting the Start of Protein $alpha$-Helices Using Machine Learning Algorithms
  37. Introduction
  38. Proteins
  39. Related Work
  40. Experiments
  41. Experimental Settings
  42. Experimental Results
  43. Conclusions and Future Work
  44. References
  45. A Data Mining Approach for the Detection of High-Risk Breast Cancer Groups
  46. Introduction
  47. Methods
  48. Data Description
  49. Decision Trees
  50. Statistical Validation
  51. Experimental Procedure
  52. Results
  53. Conclusions and Future Work
  54. References
  55. GRASP for Instance Selection in Medical Data Sets
  56. Introduction
  57. Preprocessing in KDD
  58. GRASP for IS-PS
  59. Constructive Algorithm
  60. Local Search
  61. Tabu Search
  62. Variable Neighborhood Search
  63. Experimental Results
  64. Conclusions
  65. References
  66. Expanding Gene-Based PubMed Queries
  67. Introduction
  68. Query Expansion
  69. Results
  70. Discussion
  71. Conclusions
  72. References
  73. Improving Cross Mapping in Biomedical Databases
  74. Introduction
  75. Related Work
  76. Implementation
  77. Analysis of the Coverage Improvements
  78. Usage Example
  79. Conclusion
  80. References
  81. An Efficient Multi-class Support Vector Machine Classifier for Protein Fold Recognition
  82. Introduction
  83. The Database and the Feature Vectors
  84. The SVM Classifier
  85. A Multi-class SVM
  86. One-versus-One Method
  87. Binary Decision Tree Method
  88. The Modified Approach to Multi-class Classifier
  89. Results
  90. References
  91. Feature Selection Using Multi-Objective Evolutionary Algorithms: Application to Cardiac SPECT Diagno
  92. Introduction
  93. Multi-Objective Evolutionary Algorithms
  94. Classification Methods
  95. Results and Discussion
  96. Conclusions
  97. References
  98. Phylogenetics and Sequence Analysis
  99. Two Results on Distances for Phylogenetic Networks
  100. Introduction
  101. Preliminaries
  102. On Nakhleh’s Distance $m$
  103. A Simpler Nodal Distance for Binary Networks
  104. References
  105. Cram'{e}r Coefficient in Genome Evolution
  106. Introduction
  107. Methods
  108. DNA Data
  109. Experimental Procedure
  110. Results
  111. Conclusions and Future Work
  112. References
  113. An Application for Studying Tandem Repeats in Orthologous Genes
  114. Introduction
  115. Methods
  116. Discussion
  117. Conclusion
  118. References
  119. Accurate Selection of Models of Protein Evolution
  120. Introduction
  121. Materials and Methods
  122. Results
  123. Discussion
  124. Conclusions
  125. References
  126. Scalable Phylogenetics through Input Preprocessing
  127. Motivation
  128. Methods
  129. Stand-Alone Algorithms
  130. The Supertree Approach
  131. Case Study: Human Mitochondrial DNA
  132. Structural Properties
  133. Materials and Methods
  134. Results
  135. Discussion and Future Work
  136. References
  137. The Median of the Distance between Two Leaves in a Phylogenetic Tree
  138. Introduction
  139. Preliminaries
  140. Main Result
  141. Conclusions
  142. References
  143. {it In Silico} AFLP: An Application to Assess What Is Needed to Resolve a Phylogeny
  144. Introduction
  145. Methods
  146. Results and Conclusions
  147. References
  148. Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their
  149. Introduction
  150. Language Models
  151. Developed Work
  152. Local Models
  153. Global Models
  154. Prediction Process
  155. Experimental Results
  156. Conclusions and Future Work
  157. References
  158. Biomedical Applications
  159. Structure Based Design of Potential Inhibitors of Steroid Sulfatase
  160. Introduction
  161. Docking Studies
  162. Synthesis
  163. Conclusions and Future Work
  164. References
  165. Agent-Based Model of the Endocrine Pancreas and Interaction with Innate Immune System
  166. Introduction
  167. The Model
  168. Overview
  169. Compartment and Langerhans Islets
  170. Beta Cell Agent
  171. Macrophage Agent
  172. Results and Discussion
  173. Conclusions
  174. References
  175. State-of-the-Art Genetic Programming for Predicting Human Oral Bioavailability of Drugs
  176. Introduction
  177. Experiments
  178. Results and Discussion
  179. Conclusions
  180. References
  181. Pharmacophore-Based Screening as a Clue for the Discovery of New P-Glycoprotein Inhibitors
  182. Introduction
  183. Methods
  184. Pharmacophore Modeling and Virtual Screening of a Database of Compounds
  185. Flow Cytometry Using Rhodamine 123
  186. Determination of ATPase Activity
  187. Pharmacophore Hypothesis
  188. Results and Discussion
  189. References
  190. Bioinformatics Applications
  191. {it e}-BiMotif: Combining Sequence Alignment and Biclustering to Unravel Structured Motifs
  192. Introduction
  193. Related Work
  194. Methods
  195. Finding and Reporting Structured Motifs Using e-BiMotif
  196. Complexity Analysis of e-BiMotif
  197. Conclusions and Future Work
  198. References
  199. A. {it e}-BiMotif: Algorithmic Details
  200. Applying a Metabolic Footprinting Approach to Characterize the Impact of the Recombinant Protein Pro
  201. Introduction
  202. Material and Methods
  203. Growth Conditions
  204. Analytical Methods
  205. Data Processing and Statistical Analysis
  206. Results
  207. Discussion and Conclusions
  208. References
  209. Rbbt: A Framework for Fast Bioinformatics Development with Ruby
  210. Background
  211. Implementation
  212. Features
  213. Examples of Use
  214. Conclusions
  215. References
  216. Analysis of the Effect of Reversibility Constraints on the Predictions of Genome-Scale Metabolic Mod
  217. Introduction
  218. Methods
  219. Flux Balance Analysis (FBA)
  220. Classification of Reactions Using Flux Variability Analysis
  221. Results
  222. Impact of Reversibility Constrains on Model Accuracy
  223. Impact of Reversibility Constraints on Reaction Behavior
  224. Discussion
  225. References
  226. Enhancing Elementary Flux Modes Analysis Using Filtering Techniques in an Integrated Environment
  227. Introduction
  228. Elementary Modes
  229. Efm4Optflux – An EMA Plugin for the OptFluxWorkbench
  230. Case Study
  231. Conclusion
  232. References
  233. Genome Visualization in Space
  234. Introduction
  235. Material and Methods
  236. Sequence Data
  237. Representation Method
  238. Results and Discussion
  239. Conclusion
  240. References
  241. A Hybrid Scheme to Solve the Protein Structure Prediction Problem
  242. Introduction
  243. Knowledge-Based Methods
  244. The Proposed {it ab initio} Multi-objective Approach
  245. Experimental Results
  246. Conclusions
  247. References
  248. Author Index

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Miguel Rocha,Florentino Fernandez Riverola,Hagit Shatkay,Juan Manuel Corchado,Bioinformatics