ライフサイエンスコーパス: biophysically

1 pod crustaceans has been studied extensively biophysically.

2 ed the recombinant protein biochemically and biophysically.

3 haracterize its components biochemically and biophysically.

4 peptides have been thoroughly characterized biophysically.

5 conformation changes is not well understood biophysically.

6 trations and characterized biochemically and biophysically.

7 e widely different phenotypes clinically and biophysically.

8 aintained more of an rSP-C surfactant in the biophysically active form.

9 ung injury and the amount of large-aggregate biophysically active surfactant in adult lungs.

10 The biophysically altered dermis increased myofibroblast act

11 protein were made and were biochemically and biophysically analyzed.

12 timing in integrate-and-fire units and in a biophysically and anatomically detailed model of a corti

13 Here, using biophysically and anatomically realistic computational m

14 We compare biophysically and energetically the cellular responses t

15 though mammalian TRPM7 is well characterized biophysically and its pivotal role in cancer, ischemia a

16 mplexes of ERBB receptors have been observed biophysically and offer a theoretical route for ERBB2 ph

17 apses formed by striatopallidal neurons were biophysically and pharmacologically heterogeneous.

18 Here, we biophysically and structurally characterize the full-len

19 uromuscular junctions contain two spatially, biophysically, and pharmacologically distinct subtypes o

20 these proteins has been fully characterized biophysically, and thus the precise effects on molecular

21 s in our laboratory and therefore provides a biophysically based account of the underlying ionic curr

22 Biophysically based computational modeling of the heart,

23 logical mechanisms underpinning contraction, biophysically based computational models are fitted to s

24 in vivo and in vitro experiments, as well as biophysically based computer models that have been used

25 such flexible behavior, we have developed a biophysically based decision-making network model of spi

26 It provides: (a) biophysically based explanations of putative mechanisms

27 The link between experimental data and biophysically based mathematical models is key to comput

28 We develop a biophysically based model of the neurophonic that accoun

29 Using a biophysically based model, we show how top-down signals

30 successful elements of model translation for biophysically based models and the emerging supporting t

31 and discusses insights and predictions from biophysically based models.

32 Biophysically based multicompartmental models of princip

33 le-organ function, we have developed a novel biophysically based multiscale electromechanical model o

34 inical data on BG and PD to begin to build a biophysically based network model of pallidosubthalamic

35 Using a biophysically based network model of spiking neurons, we

36 Here, we use biophysically based simulations to explore the possible

37 Previously, we developed a biophysically-based model of a binaural brainstem nucleu

38 eceptor (LILR)B1 and LILRB2 immune receptors biophysically, biochemically, and by FACS staining.

39 and dynamic antero-posterior asymmetries to biophysically characterize both resiliency to laser pert

40 Here, we biophysically characterize the carboxyl-terminal domain

41 channels remain among the least studied and biophysically characterized channels.

42 0-kDa protein that also binds heme, has been biophysically characterized for its tendency to form hig

43 y expressed recombinant protein fragment and biophysically characterized in comparison to its wild-ty

44 previous observations, we biochemically and biophysically characterized the interaction between PC4

45 p104 as a novel tubulin-binding protein, and biophysically characterized the interaction of Cep104 wi

46 To do so, we have structurally and biophysically characterized the interaction of MerB with

47 e mutated proteins have been kinetically and biophysically characterized.

48 VGLUT1 and VGLUT2, were recently cloned and biophysically characterized.

49 Nuclear mechanosensing encompasses biophysically complex pathways that often converge on th

50 Here, we construct a simplified, biophysically consistent, reaction-diffusion model of ch

51 Our study presents a biophysically constrained model of how the interaction o

52 the electrical output of neurochemically and biophysically defined LH cells in mouse brain slices.

53 nic model where anergic B cells respond to a biophysically defined lysozyme epitope displayed on both

54 ttle is known about how prior beliefs impact biophysically described processes in the presence of neu

55 A previously developed biophysically detailed attractor network exhibits sponta

56 Using this biophysically detailed cohort of models we highlight the

57 We have used a biophysically detailed compartmental model to investigat

58 In our biophysically detailed compartmental model, active dendr

59 Here, we use a biophysically detailed computational model of the presyn

60 Using a biophysically detailed computational model, we were not

61 Through biophysically detailed computer modelling, this study in

62 A biophysically detailed heart-torso model was generated f

63 gations were conducted using a population of biophysically detailed human models incorporating variab

64 We used a biophysically detailed human ventricular model to determ

65 precise timing of on- or offset, by using a biophysically detailed large-scale (19,600 model neurons

66 ach facilitates the use of biochemically and biophysically detailed mathematical models to describe a

67 In this study, we used a biophysically detailed model of the human atria and tors

68 In this study we present a biophysically detailed model of the normal canine ventri

69 Simulations of biophysically detailed neuron models show that frequency

70 cale model of cardiac tissue incorporating a biophysically detailed three-dimensional model of the ve

71 re is an effort to build an anatomically and biophysically detailed virtual heart, and, although ther

72 nans (CDA) on arrhythmia susceptibility in a biophysically detailed, 3D computer model of the human a

73 Here, a biophysically detailed, thermodynamically consistent mod

74 Using biophysically-detailed human atria computer models, this

75 Here we systematically structurally and biophysically dissected myoc-OLF to better understand it

76 The NMDAR subunits NR2A and NR2B are biophysically distinct and differentially expressed duri

77 nt recordings, mIMCD-3 cells displayed three biophysically distinct Cl(-)-selective currents, which w

78 ow the presence of two pharmacologically and biophysically distinct Cl- currents that could be specif

79 e cells in the cat striate cortex in vivo, a biophysically distinct class of pyramidal neuron termed

80 tion of spiny projection neurons composed of biophysically distinct GABAAfast and GABAAslow component

81 Neurons were divided into two biophysically distinct groups based on their frequency-d

82 Measurements of three biophysically distinct K(+) currents revealed a depolari

83 e present in BMs, creating biochemically and biophysically distinct structures that serve a wide vari

84 muscarinic receptors selectively modulate a biophysically distinctive subtype of L-type Ca2+ channel

85 Biophysically, even though neuronal fractional different

86 Using a biophysically explicit, multiscale model of olfactory bu

87 e propose a CMOS circuit implementation of a biophysically grounded neuromorphic (iono-neuromorphic)

88 Using an established, biophysically informed model of a competitive attractor

89 lated a perturbation of neural dynamics in a biophysically informed model of decision-making through

90 To fill this gap, we investigated a biophysically inspired, metaplastic synaptic model withi

91 d medial and lateral temporal cortices, were biophysically intact compared with those of control subj

92 tractility is a physiologically relevant and biophysically interesting process.

93 lding sequence-to-affinity models based on a biophysically interpretable and extensible model of prot

94 (ii) Pseudo-energies remain biophysically interpretable and hold positional informat

95 sed from brain tumor cells are biochemically/biophysically like other exosomes and have immune-modula

96 t in plants, as in bacteria, crystallization biophysically limits polymerization.

97 of nonmammalian VSPs have been characterized biophysically, mammalian VSPs are less well understood a

98 Using biophysically measured FAS distributions and swelling si

99 Our biophysically motivated model provides a more comprehens

100 We develop a pair of biophysically motivated ODE models of viral-host populat

101 yces cerevisiae, we have validated that this biophysically motivated use of evolutionary conservation

102 sistent with the activation process observed biophysically on the metabotropic glutamate receptor 2 h

103 Biophysically, our results suggest that the stabilities

104 these channels differ pharmacologically and biophysically, particularly in inactivation kinetics.

105 Imbalanced plasticity is biophysically plausible and leads to more efficient syna

106 el using coupled leaky integrator units with biophysically plausible assumptions about the effect of

107 Thus, we show that a biophysically plausible circuit model can reconstruct co

108 wo-variable neural model offers a simple yet biophysically plausible framework for studying perceptua

109 A biophysically plausible implementation of such a first-i

110 parse coding hypothesis, when coupled with a biophysically plausible implementation, can provide a un

111 Here we adapt a biophysically plausible model of decision-making to pred

112 Using a biophysically plausible model, we link these biases to s

113 new means of linking clinical symptoms with biophysically plausible models of neural circuitry and,

114 We investigated activity in a biophysically plausible network model that transforms in

115 We have reproduced this behavior in a biophysically plausible network model.

116 the spike-based approach can be extended to biophysically plausible networks.

117 g inhibitory interneurons that are much more biophysically plausible.

118 calmodulin dynamics within an idealised, but biophysically-plausible, dendritic spine, we show that S

119 We developed a biophysically realistic and detailed computational model

120 oding scheme based on network simulations of biophysically realistic compartmental models of VS cells

121 ly, we created a neuroanatomically detailed, biophysically realistic computational model of hippocamp

122 Next, we use a biophysically realistic computational model to explain t

123 A biophysically realistic computational model using data d

124 simonious hypothesis for this disruption via biophysically realistic computational modeling, namely c

125 d underlying neural dynamics, we developed a biophysically realistic computational SI model that cont

126 hanisms of decision making, I investigated a biophysically realistic cortical network model for a vis

127 gated a simplified two-variable version of a biophysically realistic cortical network model of decisi

128 n by analyzing the dynamics of a large-scale biophysically realistic cortical network model subjected

129 ties of the TBI-induced epileptogenesis in a biophysically realistic cortical network model with dyna

130 To this aim, we constructed a biophysically realistic excitatory-inhibitory network ab

131 We generated biophysically realistic fly photoreceptor models, which

132 A novel, biophysically realistic model for early-stage, acetylcho

133 Simulations of a biophysically realistic model of a cerebellar Purkinje c

134 To quantitatively examine this question, a biophysically realistic model of an idealized central ax

135 Backrubs can therefore provide a biophysically realistic model of local backbone flexibil

136 We have developed a biophysically realistic model of receptor activation at

137 (A)-mediated excitation, we built a detailed biophysically realistic model of the CA1 pyramidal neuro

138 Here, we use a large-scale, biophysically realistic model of the epileptic rat denta

139 ther, our experimental data and results from biophysically realistic modeling support the idea that h

140 In this study, using biophysically realistic models of the thalamocortical ne

141 g the memristors full potential for building biophysically realistic neural processing systems.

142 esent a systematic method to reduce complex, biophysically realistic neuron models to more tractable,

143 By implementing biophysically realistic neuron models, we study how dend

144 vity of intrinsic cortical connections among biophysically realistic neurons can account for some of

145 as priors in Bayesian inference to estimate biophysically realistic parameter values based on dynami

146 cells, the channel must be tethered for all biophysically realistic parameters of the membrane.

147 nd corresponding stochastic simulations from biophysically realistic photoreceptor models.

148 he LTD-based recognition of PF patterns in a biophysically realistic Purkinje-cell model.

149 Furthermore, our model provides a biophysically realistic solution to the MEG signal and c

150 ions of noisy and spiking neurons coupled by biophysically realistic synapses.

151 study shows that the fitness landscape of a biophysically realistic system is extremely complex, wit

152 Employing a biophysically realistic, computational model of SACs, wh

153 Morphologically and biophysically realistic, computational models of octopus

154 Here, we present a simple, biophysically relevant model of retinal contrast adaptat

155 f sequence replay depends on a confluence of biophysically relevant parameters including stimulus dur

156 i-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substate

157 N4 in these cells, and indicate that I(h) is biophysically similar in morphologically diverse retinal

158 eptors are shown to be pharmacologically and biophysically similar to 'classic' strychnine-sensitive,

159 Ca2+-selective conductance, I(ORCa), that is biophysically similar to TRPM7 currents.

160 ed evoked and miniature responses and verify biophysically that these changes correspond to an increa

161 In this study, we characterized biophysically the binding of S100A1, S100A2, S100A4, S10

162 Biophysically, these changes translate into an increase

163 STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic i

164 erase site of D-DT and its homologue MIF are biophysically very different, 4-iodo-6-phenylpyrimidine