LNCS 2950 - Aspects of Molecular Computing (Frontmatter Pages)

More documents

Recommendations

Info

70 Alessandra Carbone and Nadrian C. Seeman a representative collection of shapes. Algorithms have been developed successfully to produce that self-assemble into these and other motifs [36]. Branched molecules are tiles constituted by several single strands which self-assemble along their coding sequences in a “star-like” configuration, where a tip of the star is a branch [36,51,38] (Figure 3a,c,e illustrate 2, 3 and 4-arm branched molecules). Theoretically, one might think to construct k-armed branched molecules, for any k>2, where each strand is paired with two other strands to form a pair of double-helical arms; in practice, molecules with 6 arms have been reported, but larger ones are under construction. The angles between the arms are known to be flexible in most cases. If one adds sticky ends to a branched molecule, i.e. single stranded extensions of a double helix, a cluster is created that contains specifically addressable ends [36]. This idea is illustrated in Figure 9, where a 4-arm branched junction with two complementary pairs of sticky ends self-assembles to produce a quadrilateral. Fig. 9. Formation of a 2-dimensional lattice (right) from a 4-arm branched junction (left). X is a sticky end and X ′ is its complement. The same relationship holds for Y and Y ′ . X and Y are different from each other. The search for motifs based on DNA branched junctions that behave as though they are “rigid” while in the test tube, led to the design of several DNAmolecules, and some are illustrated in Figure 8. Rigid shapes impose strong limitations on the design of suitable molecular tiles; roughly speaking, a rigid, or tense, object is a 3-dimensional solid that does not undergo deformations: we ask that if its 1-dimensional faces do not undergo deformation, then no deformation exists. For a tetrahedron or any convex deltahedron, it is easy to see that no change of the angles between edges (edges are 1-dimensional faces for the tetrahedron) can take place without the edges be deformed. On the other hand, a cube is an example of a non-tense object since we can fix the edges (1-faces) of the cube not to undergo any deformation and still be able to deform the angles between them. Geometry of the boundaries: smooth deformations of tiles. It might be appropriate to consider assemblies which are affected by an ɛ-deformation in the shape of the tiles after binding. More precisely, a tile T ⊆ R3 is mapped in R3 by some ɛ-deformation as follows: there is an embedding ɛ : T ⊆ R3 ↦→ T ′ ⊆ R3 such that for all points x ∈ T there is a point y ∈ T ′ such that the Euclidean distance
Molecular Tiling and DNA Self-assembly 71 d(x, y)
Page 1 and 2:
Lecture Notes in Computer Science 2
Page 3 and 4:
Nata˘sa Jonoska Gheorghe Păun Grz
Page 5 and 6:
Thomas J. Head
Page 7 and 8:
VIII Preface portant to keep in min
Page 9 and 10:
X Table of Contents Formal Properti
Page 11 and 12:
Solving Graph Problems by P Systems
Page 13 and 14:
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
where Solving Graph Problems by P S
Page 27 and 28:
Page 29 and 30: Solving Graph Problems by P Systems
Page 31 and 32: Solving Graph Problems by P Systems
Page 33 and 34: Writing Information into DNA Masano
Page 35 and 36: Writing Information into DNA 25 Ham
Page 37 and 38: Writing Information into DNA 27 Fig
Page 39 and 40: Writing Information into DNA 29 Dea
Page 41 and 42: 5 Results 5.1 DNA Code for the Engl
Page 43 and 44: Writing Information into DNA 33 3.
Page 45 and 46: Writing Information into DNA 35 101
Page 47 and 48: Balance Machines: Computing = Balan
Page 49 and 50: + .. . + Balance Machines: Computin
Page 51 and 52: x Balance Machines: Computing = Bal
Page 57 and 58: 1 Balance Machines: Computing = Bal
Page 59 and 60: Eilenberg P Systems with Symbol-Obj
Page 61 and 62: 2 Definitions Definition 1. A strea
Page 69 and 70: 5 Conclusions Eilenberg P Systems w
Page 71 and 72: Molecular Tiling and DNA Self-assem
Page 73 and 74: 3 Molecular Self-assembly Processes
Page 79: Molecular Tiling and DNA Self-assem
Page 85 and 86: 8 Hierarchical Tiling Molecular Til
Page 91 and 92: References Molecular Tiling and DNA
Page 95 and 96: On Some Classes of Splicing Languag
Page 113 and 114: ˆxa ˆby ✬ ✩✬ ✩ a b x y
Page 117 and 118: The Power of Networks of Watson-Cri
Page 129 and 130: Fixed Point Approach to Commutation
Page 131 and 132:
Fixed Point Approach to Commutation
Page 133 and 134:
Page 135 and 136:
Here the last one holds if and only
Page 137 and 138:
Page 139 and 140:
� � � � � Fixed Point App
Page 141 and 142:
Page 143 and 144:
Remarks on Relativisations and DNA
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
Splicing Test Tube Systems and Thei
Page 151 and 152:
Splicing Test Tube Systems 141 the
Page 153 and 154:
Splicing Test Tube Systems 143 to a
Page 155 and 156:
Splicing Test Tube Systems 145 6. R
Page 157 and 158:
Splicing Test Tube Systems 147 (c)
Page 159 and 160:
I0 Ai i Splicing Test Tube Systems
Page 161 and 162:
Splicing Test Tube Systems 151 4. J
Page 163 and 164:
Digital Information Encoding on DNA
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177 and 178:
DNA-based Cryptography Ashish Gehan
Page 179 and 180:
DNA-based Cryptography 169 concern.
Page 181 and 182:
DNA-based Cryptography 171 The one-
Page 183 and 184:
DNA-based Cryptography 173 of DNA t
Page 185 and 186:
DNA-based Cryptography 175 Fig. 3.
Page 187 and 188:
DNA-based Cryptography 177 the comp
Page 189 and 190:
DNA-based Cryptography 179 can be c
Page 191 and 192:
DNA-based Cryptography 181 4.4 DNA-
Page 193 and 194:
DNA-based Cryptography 183 Fig. 7.
Page 195 and 196:
DNA-based Cryptography 185 offer li
Page 197 and 198:
DNA-based Cryptography 187 30. C. M
Page 199 and 200:
Splicing to the Limit Elizabeth Goo
Page 201 and 202:
Splicing to the Limit 191 molecular
Page 203 and 204:
Splicing to the Limit 193 Discussio
Page 205 and 206:
Example 9. The splicing rules are S
Page 207 and 208:
−2α � kNNk = −2αMN, k α
Page 209 and 210:
Finally we define the limit languag
Page 211 and 212:
6 Conclusion Splicing to the Limit
Page 213 and 214:
Formal Properties of Gene Assembly
Page 215 and 216:
(a) (b) Formal Properties of Gene A
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
n-Insertion on Languages Masami Ito
Page 225 and 226:
n-Insertion on Languages 215 3. ∀
Page 227 and 228:
n-Insertion on Languages 217 Theore
Page 229 and 230:
Transducers with Programmable Input
Page 231 and 232:
Page 233 and 234:
1 01 s 0 Transducers with Programma
Page 235 and 236:
order β l Transducers with Program
Page 237 and 238:
Page 239 and 240:
Page 241 and 242:
Page 243 and 244:
Page 245 and 246:
Page 247 and 248:
start tile Transducers with Program
Page 249 and 250:
Page 251 and 252:
Methods for Constructing Coded DNA
Page 253 and 254:
Page 255 and 256:
u u Methods for Constructing Coded
Page 257 and 258:
Page 259 and 260:
Page 261 and 262:
Page 263 and 264:
Page 265 and 266:
On the Universality of P Systems wi
Page 267 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
Page 275 and 276:
Page 277 and 278:
An Algorithm for Testing Structure
Page 279 and 280:
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
Page 287 and 288:
Page 289 and 290:
Definition 1. Define the relation
Page 291 and 292:
280 Manfred Kudlek Definition 5. Co
Page 293 and 294:
On Languages of Cyclic Words 283 Th
Page 295 and 296:
On Languages of Cyclic Words 285 No
Page 297 and 298:
On Languages of Cyclic Words 287 Th
Page 299 and 300:
A DNA Algorithm for the Hamiltonian
Page 301 and 302:
Page 303 and 304:
Page 305 and 306:
Page 307 and 308:
Formal Languages Arising from Gene
Page 309 and 310:
Page 311 and 312:
Page 313 and 314:
Page 315 and 316:
Page 317 and 318:
Page 319 and 320:
A Proof of Regularity for Finite Sp
Page 321 and 322:
Page 323 and 324:
Page 325 and 326:
--- ◦ ❄ ⊗ γ ✲ A Proof of R
Page 327 and 328:
Page 329 and 330:
The Duality of Patterning in Molecu
Page 331 and 332:
The Duality of Patterning in Molecu
Page 333 and 334:
Membrane Computing: Some Non-standa
Page 335 and 336:
where: Membrane Computing: Some Non
Page 337 and 338:
where: Membrane Computing: Some Non
Page 339 and 340:
Page 341 and 342:
Page 343 and 344:
Page 345 and 346:
Page 347 and 348:
Page 349 and 350:
The P Versus NP Problem Through Cel
Page 351 and 352:
Page 353 and 354:
Page 355 and 356:
Page 357 and 358:
Page 359 and 360:
Page 361 and 362:
Page 363 and 364:
Realizing Switching Functions Using
Page 365 and 366:
Realizing Switching Functions Using
Page 367 and 368:
AND Gate Realizing Switching Functi
Page 369 and 370:
NOR Gate Realizing Switching Functi
Page 371 and 372:
Plasmids to Solve #3SAT Rani Siromo
Page 373 and 374:
Plasmids to Solve #3SAT 363 A comme
Page 375 and 376:
Plasmids to Solve #3SAT 365 from th
Page 377 and 378:
Communicating Distributed H Systems
Page 379 and 380:
Page 381 and 382:
Page 383 and 384:
Proof Communicating Distributed H S
Page 385 and 386:
Page 387 and 388:
Page 389 and 390:
Page 391 and 392:
Page 393 and 394:
Page 395 and 396:
Books: Publications by Thomas J. He
Page 397 and 398:
Publications by Thomas J. Head 387
Page 399 and 400:
Publications by Thomas J. Head 389
show all

LNCS 2950 - Aspects of Molecular Computing (Frontmatter Pages)

Create successful ePaper yourself

Delete template?

Save as template?