32 N. Cannata et al. The concept Receptor Protein represents the instances of proteins with a receptor function <strong>and</strong> gathering these instances is answering that question. Acknowledgments This work is supported by the Italian Investment Funds for Basic Research (FIRB) project “Laboratory of Interdisciplinary Technologies in <strong>Bio</strong>informatics” (LITBIO) <strong>and</strong> by the Loccioni Group - University of Camerino Laboratory (LULab). Many thanks to Massimo Fedeli, Sergio Gabrieli, Victor Karmanski, Cristina Lancioni <strong>and</strong> Luana Leoni for their help. References 1. Baker, C.J.O., Shaban-Nejad, A., Su, X., Haarslev, V., Butler, G.: Semantic web infrastructure for fungal enzyme biotechnologists. J. Web Sem. 4(3), 168– 180 (2006) 2. Baker, P.G., Goble, C.A., Bechhofer, S., Paton, N.W., Stevens, R., Brass, A.: An ontology for bioinformatics applications. <strong>Bio</strong>informatics 15(6), 510–520 (1999) 3. Bard, J.B.L., Rhee, S.Y.: <strong>Ontologies</strong> in biology: design, applications <strong>and</strong> future challenges. Nature Reviews Genetics 5(3), 213–222 (2004) 4. Bartocci, E., Cacciagrano, D., Cannata, N., Corradini, F., Merelli, E., Milanesi, L., Romano, P.: An Agent-based Multilayer Architecture for <strong>Bio</strong>informatics Grids. IEEE transactions on Nanobioscience 6(2), 142–148 (2007) 5. Bechhofer, S., Stevens, R.D., Lord, P.W.: Gohse: Ontology driven linking of biology resources. J. Web Sem. 4(3), 155–163 (2006) 6. Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Sci. Am. 284, 34–43 (2001) 7. Blake, J.A., Bult, C.J.: Beyond the data deluge: Data integration <strong>and</strong> bioontologies. Journal of <strong>Bio</strong><strong>medical</strong> Informatics 39(3), 314–320 (2006) 8. Bodenreider, O., Stevens, R.: <strong>Bio</strong>-ontologies: current trends <strong>and</strong> future directions. Brief <strong>Bio</strong>inform. 7(3), 256–274 (2006) 9. Boguski, M.S.: <strong>Bio</strong>informatics–a new era. Trends Guide to <strong>Bio</strong>informatics, Trends Supplement, 1–3 (1998) 10. Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C.A., Causton, H.C., Gaasterl<strong>and</strong>, T., Glenisson, P., Holstege, F.C.P., Kim, I.F., Markowitz, V., Matese, J.C., Parkinson, H., Robinson, A., Sarkans, U., Schulze-Kremer, S., Stewart, J., Taylor, R., Vilo, J., Vingron, M.: Minimum information about a microarray experiment (miame)- toward st<strong>and</strong>ards for microarray data. Nat. Genet. 29(4), 365–371 (2001) 11. Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks 30(1-7), 107–117 (1998) 12. Buetow, K.H.: Cyberinfrastructure: Empowering a ”Third Way” in <strong>Bio</strong><strong>medical</strong> Research. Science 308(5723), 821–824 (2005) 13. Butler, D.: Mashups mix data into global service. Nature 439(7072), 6–7 (2005)
Towards <strong>Bio</strong>informatics Resourceomes 33 14. Cannata, N., Corradini, F., Merelli, E.: A resourceomic grid for bioinformatics. Future Generation Comp. Syst. 23(3), 510–516 (2007) 15. Cannata, N., Corradini, F., Merelli, E., Omicini, A., Ricci, A.: An agentoriented conceptual framework for systems biology. In: Priami, C., Merelli, E., Gonzalez, P., Omicini, A. (eds.) Transactions on Computational Systems <strong>Bio</strong>logy III. LNCS (LNBI), vol. 3737, pp. 105–122. Springer, Heidelberg (2005) 16. Cannata, N., Merelli, E., Altman, R.B.: Time to organize the bioinformatics resourceome. PLoS Comput <strong>Bio</strong>l. 1(7), e76 (2005) 17. Cannataro, M., et al.: Algorithms <strong>and</strong> databases in bioinformatics: Towards a proteomic ontology. In: ITCC (1), pp. 322–328. IEEE, Los Alamitos (2005) 18. Chen, Y.-B., Chattopadhyay, A., Bergen, P., Gadd, C., Tannery, N.: The Online <strong>Bio</strong>informatics Resources Collection at the University of Pittsburgh Health Sciences Library System–a one-stop gateway to online bioinformatics databases <strong>and</strong> software tools. Nucl. Acids Res. 35(suppl. 1), D780–D785 (2007) 19. Cohen-Boulakia, S., Davidson, S.B., Froidevaux, C., Lacroix, Z., Vidal, M.-E.: Path-based systems to guide scientists in the maze of biological data sources. J. <strong>Bio</strong>informatics <strong>and</strong> Computational <strong>Bio</strong>logy 4(5), 1069–1096 (2006) 20. The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nature Genet. 25 21. de Knikker, R., Guo, Y., Li, J.-l., Kwan, A., Yip, K., Cheung, D., Cheung, K.-H.: A web services choreography scenario for interoperating bioinformatics applications. BMC <strong>Bio</strong>informatics 5(1), 25 (2004) 22. De Roure, D., Hendler, J.A.: E-science: The Grid <strong>and</strong> the Semantic Web. IEEE Intelligent Systems 19(1), 65–71 (2004) 23. De Roure, D., Jennings, N.R., Shadbolt, N.R.: The Semantic Grid: A future e-science infrastructure. Grid Computing (2003) 24. Dellavalle, R.P., Hester, E.J., Heilig, L.F., Drake, A.L., Kuntzman, J.W., Graber, M., Schilling, L.M.: INFORMATION SCIENCE: Going, Going, Gone: Lost Internet References (2003) 25. Doms, A., Schroeder, M.: GoPubMed: exploring PubMed with the Gene Ontology. Nucl. Acids Res. 33(suppl. 2), W783–W786 (2005) 26. Fang, Z., Yang, J., Li, Y., Luo, Q.m., Liu, L.: Knowledge guided analysis of microarray data, pp. 401–411 (2006) 27. Fenstermacher, D.A.: Introduction to bioinformatics. JASIST 56(5), 440–446 (2005) 28. Foster, I., Kesselman, C.: The Grid: Blueprint for a Future Computing Infrastructure. Morgan Kaufmann Publishers, San Francisco (1998) 29. Foster, I.T., Jennings, N.R., Kesselman, C.: Brain meets brawn: Why grid <strong>and</strong> agents need each other. In: AAMAS, pp. 8–15. IEEE Computer Society, Los Alamitos (2004) 30. Fox, J.A., McMillan, S., Ouellette, B.F.F.: Conductin Research on the Web: 2007 Update for the <strong>Bio</strong>informatics Links Directory. Nucl. Acids Res. 35(suppl. 2), W3–W5 (2007) 31. Galperin, M.Y.: The Molecular <strong>Bio</strong>logy Database Collection: 2007 update. Nucl. Acids Res. 35(suppl. 1), D3–D4 (2007) 32. Gao, Y., Kinoshita, J., Wu, E., Miller, E., Lee, R., Seaborne, A., Cayzer, S., Clark, T.: Swan: A distributed knowledge infrastructure for alzheimer disease research. J. Web. Sem. 4(3), 222–228 (2006) 33. Gil, Y.: On agents <strong>and</strong> grids: Creating the fabric for a new generation of distributed intelligent systems. J. Web Sem. 4(2), 116–123 (2006)
- Page 1 and 2: Amandeep S. Sidhu and Tharam S. Dil
- Page 3 and 4: Amandeep S. Sidhu and Tharam S. Dil
- Page 5 and 6: Preface The molecular biology commu
- Page 7 and 8: Preface VII biomedical systems, and
- Page 9 and 10: X Contents Mining Clinical, Immunol
- Page 11 and 12: 2 A.S. Sidhu, M. Bellgard, and T.S.
- Page 13 and 14: 4 A.S. Sidhu, M. Bellgard, and T.S.
- Page 15 and 16: 6 A.S. Sidhu, M. Bellgard, and T.S.
- Page 17 and 18: 8 A.S. Sidhu, M. Bellgard, and T.S.
- Page 19 and 20: Towards Bioinformatics Resourceomes
- Page 21 and 22: Towards Bioinformatics Resourceomes
- Page 23 and 24: Towards Bioinformatics Resourceomes
- Page 25 and 26: 2 The New Waves Towards Bioinformat
- Page 27 and 28: 2.4 Semantic Web Towards Bioinforma
- Page 29 and 30: Towards Bioinformatics Resourceomes
- Page 31 and 32: Towards Bioinformatics Resourceomes
- Page 33 and 34: Towards Bioinformatics Resourceomes
- Page 35 and 36: Towards Bioinformatics Resourceomes
- Page 37: Towards Bioinformatics Resourceomes
- Page 41 and 42: Towards Bioinformatics Resourceomes
- Page 43 and 44: A Summary of Genomic Databases: Ove
- Page 45 and 46: A Summary of Genomic Databases: Ove
- Page 47 and 48: A Summary of Genomic Databases: Ove
- Page 49 and 50: A Summary of Genomic Databases: Ove
- Page 51 and 52: A Summary of Genomic Databases: Ove
- Page 53 and 54: A Summary of Genomic Databases: Ove
- Page 55 and 56: A Summary of Genomic Databases: Ove
- Page 57 and 58: A Summary of Genomic Databases: Ove
- Page 59 and 60: Appendix A Summary of Genomic Datab
- Page 61 and 62: Protein Data Integration Problem Am
- Page 63 and 64: Protein Data Integration Problem 57
- Page 65 and 66: Protein Data Integration Problem 59
- Page 67 and 68: Protein Data Integration Problem 61
- Page 69 and 70: Fig. 3. Class Hierarchy of Protein
- Page 71 and 72: Protein Data Integration Problem 65
- Page 73 and 74: Protein Data Integration Problem 67
- Page 75 and 76: Protein Data Integration Problem 69
- Page 77 and 78: 72 L. Stanescu, D. Dan Burdescu, an
- Page 79 and 80: 74 L. Stanescu, D. Dan Burdescu, an
- Page 81 and 82: 76 L. Stanescu, D. Dan Burdescu, an
- Page 83 and 84: 78 L. Stanescu, D. Dan Burdescu, an
- Page 85 and 86: 80 L. Stanescu, D. Dan Burdescu, an
- Page 87 and 88: 82 L. Stanescu, D. Dan Burdescu, an
- Page 89 and 90:
84 L. Stanescu, D. Dan Burdescu, an
- Page 91 and 92:
86 L. Stanescu, D. Dan Burdescu, an
- Page 93 and 94:
88 L. Stanescu, D. Dan Burdescu, an
- Page 95 and 96:
90 L. Stanescu, D. Dan Burdescu, an
- Page 97 and 98:
92 L. Stanescu, D. Dan Burdescu, an
- Page 99 and 100:
94 L. Stanescu, D. Dan Burdescu, an
- Page 101 and 102:
96 L. Stanescu, D. Dan Burdescu, an
- Page 103 and 104:
98 L. Stanescu, D. Dan Burdescu, an
- Page 105 and 106:
100 L. Stanescu, D. Dan Burdescu, a
- Page 107 and 108:
102 L. Stanescu, D. Dan Burdescu, a
- Page 109 and 110:
104 L. Stanescu, D. Dan Burdescu, a
- Page 111 and 112:
106 L. Stanescu, D. Dan Burdescu, a
- Page 113 and 114:
108 L. Stanescu, D. Dan Burdescu, a
- Page 115 and 116:
110 L. Stanescu, D. Dan Burdescu, a
- Page 117 and 118:
112 L. Stanescu, D. Dan Burdescu, a
- Page 119 and 120:
114 L. Stanescu, D. Dan Burdescu, a
- Page 121 and 122:
116 L. Stanescu, D. Dan Burdescu, a
- Page 123 and 124:
118 L. Stanescu, D. Dan Burdescu, a
- Page 125 and 126:
120 L. Stanescu, D. Dan Burdescu, a
- Page 127 and 128:
122 L. Stanescu, D. Dan Burdescu, a
- Page 129 and 130:
124 L. Stanescu, D. Dan Burdescu, a
- Page 131 and 132:
126 L. Stanescu, D. Dan Burdescu, a
- Page 133 and 134:
128 L. Stanescu, D. Dan Burdescu, a
- Page 135 and 136:
130 L. Stanescu, D. Dan Burdescu, a
- Page 137 and 138:
132 L. Stanescu, D. Dan Burdescu, a
- Page 139 and 140:
134 L. Stanescu, D. Dan Burdescu, a
- Page 141 and 142:
136 L. Stanescu, D. Dan Burdescu, a
- Page 143 and 144:
138 L. Stanescu, D. Dan Burdescu, a
- Page 145 and 146:
140 L. Stanescu, D. Dan Burdescu, a
- Page 147 and 148:
Bio-medical Ontologies Maintenance
- Page 149 and 150:
Bio-medical Ontologies Maintenance
- Page 151 and 152:
Bio-medical Ontologies Maintenance
- Page 153 and 154:
Bio-medical Ontologies Maintenance
- Page 155 and 156:
Bio-medical Ontologies Maintenance
- Page 157 and 158:
Bio-medical Ontologies Maintenance
- Page 159 and 160:
TextToOnto (Maedche and Volz 2001)
- Page 161 and 162:
Bio-medical Ontologies Maintenance
- Page 163 and 164:
Bio-medical Ontologies Maintenance
- Page 165 and 166:
Bio-medical Ontologies Maintenance
- Page 167 and 168:
Bio-medical Ontologies Maintenance
- Page 169 and 170:
Bio-medical Ontologies Maintenance
- Page 171 and 172:
Bio-medical Ontologies Maintenance
- Page 173 and 174:
Extraction of Constraints from Biol
- Page 175 and 176:
Extraction of Constraints from Biol
- Page 177 and 178:
Extraction of Constraints from Biol
- Page 179 and 180:
Extraction of Constraints from Biol
- Page 181 and 182:
Extraction of Constraints from Biol
- Page 183 and 184:
Extraction of Constraints from Biol
- Page 185 and 186:
Extraction of Constraints from Biol
- Page 187 and 188:
Extraction of Constraints from Biol
- Page 189 and 190:
Extraction of Constraints from Biol
- Page 191 and 192:
Classifying Patterns in Bioinformat
- Page 193 and 194:
Classifying Patterns in Bioinformat
- Page 195 and 196:
Classifying Patterns in Bioinformat
- Page 197 and 198:
Classifying Patterns in Bioinformat
- Page 199 and 200:
Classifying Patterns in Bioinformat
- Page 201 and 202:
Classifying Patterns in Bioinformat
- Page 203 and 204:
Classifying Patterns in Bioinformat
- Page 205 and 206:
Classifying Patterns in Bioinformat
- Page 207 and 208:
Classifying Patterns in Bioinformat
- Page 209 and 210:
Classifying Patterns in Bioinformat
- Page 211 and 212:
Classifying Patterns in Bioinformat
- Page 213 and 214:
Classifying Patterns in Bioinformat
- Page 215 and 216:
Mining Clinical, Immunological, and
- Page 217 and 218:
Mining Clinical, Immunological, and
- Page 219 and 220:
Mining Clinical, Immunological, and
- Page 221 and 222:
Mining Clinical, Immunological, and
- Page 223 and 224:
Mining Clinical, Immunological, and
- Page 225 and 226:
Mining Clinical, Immunological, and
- Page 227 and 228:
Mining Clinical, Immunological, and
- Page 229 and 230:
Mining Clinical, Immunological, and
- Page 231 and 232:
Mining Clinical, Immunological, and
- Page 233 and 234:
Mining Clinical, Immunological, and
- Page 235 and 236:
Mining Clinical, Immunological, and
- Page 237 and 238:
Mining Clinical, Immunological, and
- Page 239 and 240:
Mining Clinical, Immunological, and
- Page 241 and 242:
Substructure Analysis of Metabolic
- Page 243 and 244:
Substructure Analysis of Metabolic
- Page 245 and 246:
Substructure Analysis of Metabolic
- Page 247 and 248:
Substructure Analysis of Metabolic
- Page 249 and 250:
Substructure Analysis of Metabolic
- Page 251 and 252:
Substructure Analysis of Metabolic
- Page 253 and 254:
entry compound relation subtype com
- Page 255 and 256:
Substructure Analysis of Metabolic
- Page 257 and 258:
Running Time 4500 4000 3500 3000 25
- Page 259 and 260:
Substructure Analysis of Metabolic
- Page 261 and 262:
Substructure Analysis of Metabolic
- Page 263 and 264:
6 Conclusion Substructure Analysis
- Page 265 and 266:
Substructure Analysis of Metabolic
- Page 267 and 268:
266 J.Y. Chen, S. Taduri, and F. Ll
- Page 269 and 270:
268 J.Y. Chen, S. Taduri, and F. Ll
- Page 271 and 272:
270 J.Y. Chen, S. Taduri, and F. Ll
- Page 273 and 274:
272 J.Y. Chen, S. Taduri, and F. Ll
- Page 275 and 276:
274 J.Y. Chen, S. Taduri, and F. Ll
- Page 277 and 278:
276 J.Y. Chen, S. Taduri, and F. Ll
- Page 279 and 280:
278 J.Y. Chen, S. Taduri, and F. Ll
- Page 281 and 282:
Completing the Total Wellbeing Puzz
- Page 283 and 284:
Completing the Total Wellbeing Puzz
- Page 285 and 286:
Completing the Total Wellbeing Puzz
- Page 287 and 288:
Completing the Total Wellbeing Puzz
- Page 289 and 290:
Completing the Total Wellbeing Puzz
- Page 291 and 292:
Completing the Total Wellbeing Puzz
- Page 293 and 294:
Completing the Total Wellbeing Puzz
- Page 295 and 296:
296 M. Fernandez, M. Villasana, and
- Page 297 and 298:
298 M. Fernandez, M. Villasana, and
- Page 299 and 300:
300 M. Fernandez, M. Villasana, and
- Page 301 and 302:
302 M. Fernandez, M. Villasana, and
- Page 303 and 304:
304 M. Fernandez, M. Villasana, and
- Page 305 and 306:
306 M. Fernandez, M. Villasana, and
- Page 307 and 308:
308 M. Fernandez, M. Villasana, and
- Page 309 and 310:
310 M. Fernandez, M. Villasana, and
- Page 311 and 312:
312 M. Fernandez, M. Villasana, and
- Page 313 and 314:
314 M. Fernandez, M. Villasana, and
- Page 315 and 316:
Genetic Algorithm in Ab Initio Prot
- Page 317 and 318:
Genetic Algorithm in Ab Initio Prot
- Page 319 and 320:
Genetic Algorithm in Ab Initio Prot
- Page 321 and 322:
Genetic Algorithm in Ab Initio Prot
- Page 323 and 324:
Genetic Algorithm in Ab Initio Prot
- Page 325 and 326:
Genetic Algorithm in Ab Initio Prot
- Page 327 and 328:
Genetic Algorithm in Ab Initio Prot
- Page 329 and 330:
Genetic Algorithm in Ab Initio Prot
- Page 331 and 332:
Genetic Algorithm in Ab Initio Prot
- Page 333 and 334:
Genetic Algorithm in Ab Initio Prot
- Page 335 and 336:
Genetic Algorithm in Ab Initio Prot
- Page 337 and 338:
Genetic Algorithm in Ab Initio Prot
- Page 339 and 340:
Genetic Algorithm in Ab Initio Prot
- Page 341:
Author Index Apiletti, Daniele 169