Systems Biology (Methods in Molecular Biology)

(Tina Sui) #1

Molecular-cellular network hypothesis..............217–220,
222, 234, 237, 240, 241
Molecular diffusion.......................................................277
Molecular imaging .............................337–342, 344–347,
349–351, 353, 354, 356
Monte Carlo
method....................................................................320
model.......................................................................320
Morphogenesis....................................... 8,18–21, 23, 43,
48, 50, 203, 204
Mouse............................................. 22, 24,198, 199, 291
Multi-agent simulation (MAS) paradigm...........307–325
Mutagenesis...................................................................154
Mutation................................3,6–9, 11, 16, 23, 62, 147,
156, 171, 205, 206, 217, 225, 228, 230, 232,
234, 237–240, 261


N


Network
brain network models....................................314–323
gene network...........................................................127
protein network......................................230–232, 234
Noise
intrinsic (uncorrelated)..............................60, 63, 196
extrinsic (correlated)...............................................196
Non-equilibrium (theory) .............................97,128, 183
Non-equilibrium thermodynamics..............................182
Nonlinear....................................... 62, 70, 74, 75, 81, 84,
86–89, 97–100, 112, 115, 119, 127, 128, 132,
159, 173, 177–186, 188, 190–192, 200,
203–211, 248, 249, 257, 258, 263
Non-locality...................................................................128
Nuclear Magnetic Resonance (NMR)
spectroscopy.............................207, 211, 328–335


O


Observables ..................................... 1, 17, 18, 60, 63, 68,
99, 105, 109, 110
Ontology..................................1–6, 9, 28, 293, 339, 340
Open systems.......................................................... 32, 128
Optical microscopy .....................................280, 341, 346
Ordinary differential equation (ODE) .........................72,
81, 84, 108, 135, 137, 139, 160, 174, 184, 188,
198, 223, 224, 248, 257, 258, 263
Organization (in Biology) ........................................7, 127
Overexpression...........................150–154, 264, 268, 289
Overfitting........................................................57–59, 252


P


Parameters
model................................................. 57, 58,251, 308
model control parameters..............63,132, 133, 136,
138–140, 145, 157, 159, 160, 162, 163, 182


Partitioning (dynamic partitioning)...........279, 284, 286
Phase transition
biological phase transition......................................142
Phenotype
differentiation...............................................28, 95, 98
switch................................................................ 99, 217
Polymerase chain reaction (PCR)......................... 29, 264
Positive feedback loops.......................227, 234–236, 238
Principal Component Analysis (PCA) ....................59–63,
68, 332, 333

R
Reaction-Diffusion (RD)...........................173, 194–196,
204, 207, 210
Reactive oxygen species (ROS) ...........................150, 157
Reductionism.................................................................. 41
Reductionist (approach) ......................................129, 172
Region Of Interest (ROI).........................281–285, 287,
319, 320, 354
Respiration rate (RR)....................................................146
RNA sequence analysis........................................291–304
Robustness....................................... 8, 96,102, 128, 133,
134, 142, 148, 153, 156, 157, 159, 162, 164,
173, 217, 238, 251, 258, 340
R statistical computing language.................................292

S
Saddle............................................... 85, 86, 96,120, 141,
142, 164, 191, 241
Self-organization ...............132, 142, 156, 159, 163, 308
Sensitivity (to fluctuations)...........................................278
Shape................................................ 21, 50, 65,102, 103,
105, 106, 114, 115, 143, 144, 176, 194, 218,
220, 222, 241, 266, 308, 310–312, 335, 347, 348
Shape parameters..................................................346, 347
Signaling............................................104, 126, 129, 176,
179–181, 196, 219, 221, 222, 234, 237, 252,
259, 260, 265, 268, 270
Signaling pathways.....................................129, 221, 222,
234, 237, 252, 259, 260, 268, 270
Sloppy models................................................................. 57
Smoothing.....................................................................208
Solidity...........................................................................348
Somatic mutation theory (SMT)..............................3, 16,
22, 23, 206–208
Spatio-temporal image correlation spectroscopy
(STICS)..............................................................278
State
stable state....................................100, 161, 179, 186,
217, 218, 220, 223–225, 227, 228, 232
state space.............................................. 44, 45, 48, 54
Stochastic dynamical systems........................................239
Stochasticity.................................... 31, 91,173, 196–198

SYSTEMSBIOLOGY
Index^363
Free download pdf