1 involvement supports a previously published
mathematical model.
2 accompanying polysaccharide synthesis with a
mathematical model.
3 ssure generation with a previously validated
mathematical model.
4 us to construct an improved, more predictive
mathematical model.
5 ate the formation of demarcation line with a
mathematical model.
6 cretion both in vitro and in vivo by using a
mathematical model.
7 ore the predictions of this framework with a
mathematical model.
8 e at diagnosis, as reflected in a predictive
mathematical model.
9 us virus, we incorporated this effect into a
mathematical model.
10 two monomers and explicitly rationalized by
mathematical modeling.
11 vaccination programmes is routinely based on
mathematical modelling.
12 ms, we developed three biologically anchored
mathematical models:
1) parallel activation of Fshb inhi
13 Mathematical models accounting for this heterogeneity de
14 However, few
mathematical models address the impact of vaccination on
15 nation of kinetic parameters and data-driven
mathematical modelling allowed us to obtain detailed inf
16 on (1) an evolutionary analysis of a simple
mathematical model and (2) simulation experiments of an
17 Here, the authors use a
mathematical model and field data from a seasonally stra
18 Here, using
mathematical modeling and digital experimental evolution
19 Here, using a combination of
mathematical modeling and experiment, we show that there
20 Specifically, through
mathematical modeling and experimental validation, we id
21 Prominent among them are
mathematical modeling and laboratory experiments that co
22 ally analyzes the latest developments in the
mathematical modeling and simulation techniques that hav
23 We explored, through
mathematical modeling and simulations, the size of poten
24 Here we use a joint
mathematical modelling and experimental approach to asse
25 Through
mathematical modelling and experiments with Vibrio chole
26 Here we combine
mathematical modelling and lab experimentation to invest
27 is to highlight emerging concepts, including
mathematical modelling and the molecular engineering of
28 Mathematical models and experimental insights rationaliz
29 Using
mathematical models and experiments, we suggest that the
30 Here, we formalized these theories into
mathematical models and performed biological experiments
31 rtantly, bootstrapping is independent of the
mathematical model,
and thus generalizable beyond enzyme
32 d bed of identical grains using simulations,
mathematical modeling,
and experiments.
33 The
mathematical model applied here accounts for transport o
34 A
mathematical model applying a Markov Chain Monte Carlo m
35 We use a
mathematical modelling approach to estimate the impact o
36 Previous
mathematical modeling approaches demonstrated that diffe
37 ot intuitive, exemplifying the importance of
mathematical modelling approaches.
38 Mathematical models are excellent tools to meet this dem
39 We used
mathematical modeling as a theoretical framework to brid
40 Here we present a theoretical and
mathematical model based on an extension of evolutionary
41 A
mathematical model based on our experimental data demons
42 We build a
mathematical model based on these data and in the aggreg
43 A
mathematical model based on trolox pattern was developed
44 Ca(2+) influx, we generated a comprehensive
mathematical model,
based on experimental Ca(2+) measure
45 utant embryos and combined these data with a
mathematical model-
based computational screen to test hy
46 onitored on a large scale through the use of
mathematical models by way of differential equations, fo
47 A
mathematical model can explain this behavior based on th
48 one network designed with the aid of a novel
mathematical model can substantially reduce the AED deli
49 Here, we demonstrate how
mathematical models can be integrated with data to addre
50 Mathematical models can facilitate an integrative unders
51 Our
mathematical model captures the underlying dynamics of t
52 f the complexity of the fibrinolytic system,
mathematical models closely tied with experiments can be
53 Using a
mathematical model,
closely tied to experimental work, w
54 Mathematical modeling combined with experimental analysi
55 t a drone network designed with the aid of a
mathematical model combining both optimization and queui
56 icine tools-such as genomics, radiomics, and
mathematical modelling-
could open new doors to personali
57 Mathematical modeling demonstrated that lower CAR sensit
58 A
mathematical model demonstrates that periodic spatial di
59 A
mathematical model describing the decline in volatile co
60 whether the inclusion of humidity forcing in
mathematical models describing influenza transmission im
61 hese factors were correlated in a predictive
mathematical model designed to guide prognosis on the ba
62 Surprisingly, we found that a leading
mathematical model,
developed with traditional approache
63 However, decades-old experimental work and
mathematical modeling document methods to calculate both
64 ng, qPCR and experimental xenodiagnoses with
mathematical models,
Doehl et al. argue that the patchy
65 Our
mathematical model explained how ADCS enhanced the inhib
66 Mathematical modeling explains these results using addit
67 We developed a novel
mathematical model explicitly considering the heterogene
68 rimental data for a sample population, and a
mathematical model fit to aggregate data from that sampl
69 This article describes the
mathematical model for an immunochromatographic assay fo
70 ulture, there is not a standard broadly used
mathematical model for bacterial populations growing in
71 A
mathematical model for calculating fluorophore ORF and s
72 , our experimental data, when coupled with a
mathematical model for collective migration, shows that
73 The results were incorporated into a
mathematical model for FMD, in a cattle herd, to evaluat
74 survey of animal species and a parameterised
mathematical model for humans, we suggest that combined
75 We established a
mathematical model for IL-1beta-induced activation of th
76 This approach is based upon a new
mathematical model for Lux activity, that includes the a
77 Based on these results, we developed a
mathematical model for protrusion waves in which local d
78 We present a more general
mathematical model for real-time high-capacity ride-shar
79 In this paper, we present a spatio-temporal
mathematical model for simulating the formation and grow
80 We have developed and applied a novel
mathematical model for SPR data treatment that enables d
81 resent for the first time a fully consistent
mathematical model for the genesis of the pattern by cou
82 We developed a climate-driven R0
mathematical model for the transmission risk of Zika vir
83 Mathematical models for ECM-integrin binding kinetics th
84 reactions; it is therefore necessary to use
mathematical models for holistic studies.
85 ecognition techniques were used to construct
mathematical models for predicting the type of milk (org
86 etic and pharmacodynamic (PK/PD) models with
mathematical models for the population-level transmissio
87 Here, we review how
mathematical models give insight into the dynamics of th
88 nventional clinical instruments to develop a
mathematical model guided by cellular mechanisms that qu
89 Mathematical modeling has been instrumental in identifyi
90 ve experimental data, force measurements and
mathematical modeling has changed our understanding of m
91 Previous
mathematical modeling has suggested that the morphology
92 Mathematical modelling has become an established tool fo
93 High-throughput sequencing and
mathematical modelling have yielded detailed genome-wide
94 lp overcome this complexity, systems biology
mathematical models have been generated for predicting b
95 Mathematical modeling helps provide a mechanistic unders
96 Mathematical modeling highlights the role of these three
97 Here, we examine by means of
mathematical modeling how this interaction influences se
98 Current
mathematical models,
however, do not fully address the p
99 We use
mathematical modeling in combination with physiological
100 The use of
mathematical models in biology is referred to as systems
101 pact of such dynamical trade-offs by a novel
mathematical model incorporating de novo mutations for b
102 We use a
mathematical model incorporating effects of light, circa
103 Mathematical modeling indicates that accentuated costs t
104 Integration of experiments and
mathematical modeling indicates that extracellular potas
105 Mathematical modelling indicates that tumour spatial str
106 Furthermore, a
mathematical model is constructed for the simulation of
107 Here, a computational and
mathematical model is provided to test whether passive m
108 olecular biology, computational biology, and
mathematical modeling is an efficient approach to identi
109 machinery with organelle tracking data in a
mathematical model,
iterating with knockdown cell models
110 KEY POINTS: A
mathematical model of a small conductance Ca(2)(+) -acti
111 n metabolism and breast cancer, a predictive
mathematical model of an expanded iron homeostasis pathw
112 present, to our knowledge, a new multiscale
mathematical model of arterial contractility accounting
113 Results were interpreted using a
mathematical model of binding-diffusion mediated arteria
114 From these metrics, we developed a
mathematical model of cancer biomarker kinetics that acc
115 Indeed, our biphasic
mathematical model of Cdc42 polarization predicts that p
116 estinal tract was used in association with a
mathematical model of chemical reaction kinetics.
117 The present paper develops a
mathematical model of CP based on a dynamic network that
118 These results were validated using a
mathematical model of CSNs, including IKD and TRPM8, sho
119 Using a
mathematical model of HIV dynamics, we demonstrate that
120 With a network-based
mathematical model of HIV, Neisseria gonorrhoeae (NG), a
121 We used a
mathematical model of HPV 6/11/16/18 sexual transmission
122 hat the bifurcation properties of a standard
mathematical model of lateral inhibition can lead to sta
123 A
mathematical model of measles transmission and vaccine s
124 We employed these data to devise and test a
mathematical model of melanopsin's involvement in form v
125 METHODS AND Using an existing
mathematical model of MiP, we combined estimates of the
126 In this paper, we analyze a highly detailed
mathematical model of mouse ventricular myocytes to disc
127 Here we present a
mathematical model of neutrophil signal relay that focus
128 A
mathematical model of phagocytosis suggests that hFcgamm
129 METHODS AND We combined an established
mathematical model of Plasmodium falciparum transmission
130 of 5-HT2CRs in incentive motivation using a
mathematical model of progressive ratio (PR) responding
131 We use a
mathematical model of smallholders' fields to determine
132 To investigate this, we developed a
mathematical model of the adrenal steroidogenic regulato
133 This observation formed the basis for a new
mathematical model of the BG, quantitatively fitted to t
134 describe and illustrate this strategy via a
mathematical model of the cell cycle that includes descr
135 A
mathematical model of the circadian pacemaker and its re
136 re we construct and analyze a coarse-grained
mathematical model of the fission yeast ring to explore
137 Here we present a
mathematical model of the fluid flow and of the micro-be
138 We develop a
mathematical model of the function of the 1,2-propanedio
139 ng total aromatase inhibition was input to a
mathematical model of the hormonal hypothalamus-pituitar
140 d that might integrate these findings with a
mathematical model of the interpersonal influence system
141 ata informed changes in our well-established
mathematical model of the rabbit myocyte.
142 A dynamic
mathematical model of the SA-mediated plant immunity net
143 beating (using micro-beads as tracers) and a
mathematical model of this fluid flow, presented in grea
144 We propose a cell-based
mathematical model of tissue growth to investigate the s
145 transformation-specific factors to develop a
mathematical model of Yan occupancy at chemical equilibr
146 We combine
mathematical modeling of genome evolution with comparati
147 Flow cytometric assessment and
mathematical modeling of intraerythrocytic parasite deve
148 Overall, our data support the use of
mathematical modeling of intratumoral Darwinian interact
149 In conclusion, using
mathematical modeling of published and newly generated d
150 Mathematical modeling of soft actuators is an area that
151 This study employs
mathematical modelling of endoscopic and histological da
152 In this study, we consider randomness in the
mathematical modelling of forest trees by incorporating
153 Mathematical modelling of human islets suggests that 23%
154 Mathematical modelling of nutritional mutualisms has gre
155 More specifically, we developed
mathematical models of acquired and inherited long-QT sy
156 Mathematical models of emergent pathogens allow forecast
157 d will be very useful as input parameters in
mathematical models of food degradation in the human sto
158 Complex
mathematical models of interaction networks are routinel
159 We constructed various
mathematical models of mTORC1 activation mediated by Akt
160 ness and cognitive impairments, but existing
mathematical models of sleep and cognitive performance d
161 Most conceptual and
mathematical models of soil vapor intrusion assume that
162 Here we develop
mathematical models of Tfh cells in germinal centers to
163 Mathematical models of the dynamics of a drug within the
164 Mathematical models of the response of zeaxanthin- and l
165 surement and treatment, difficult-to-compare
mathematical models of underlying mechanisms, and unknow
166 We developed
mathematical models of viral dynamics upon initial oral
167 Finally, we demonstrate that when leading
mathematical models of working memory are adjusted to ac
168 equiring pure compound synthesis, or complex
mathematical models or in-silico simulations.
169 c techniques, quantitative cell imaging, and
mathematical modeling,
our study in Caulobacter crescent
170 normal control tissues (aorta, psoas) and in
mathematical models (
P < 0.01).
171 visor (EMMA), consisting of patient-specific
mathematical models parameterized by an ex vivo assay th
172 Additionally, we developed a
mathematical model,
parameterized by cell viability expe
173 ty in tumor growth, as well as errors in the
mathematical model,
perhaps from an oversimplification o
174 the field contributed their experimental and
mathematical modelling perspectives and discussed emergi
175 Unfortunately, standard
mathematical modeling practices mask the importance of p
176 in line with experimental observations, the
mathematical model predicted a significantly higher half
177 Mathematical modeling predicted that the latent reservoi
178 Mathematical modeling predicted the existence of an affi
179 Mathematical modelling predicted that ecDNA amplificatio
180 Mathematical modelling predicted that tubular Na(+) reab
181 Mathematical modelling predicted that tubular Na(+) reab
182 A
mathematical model predicts that colonies formed solely
183 Mathematical modeling predicts that dependence of signal
184 Mathematical modelling predicts substantial beneficial h
185 The
mathematical models presented can explain a number of pr
186 cally motivated, control strategies, using a
mathematical model previously fitted to the spread of ci
187 Our
mathematical modeling proposes that the observed spectra
188 Mathematical modeling provided estimates of receptor agg
189 s work we derive, to our knowledge, a new 1D
mathematical model quantifying canal biomechanics based
190 In the present work, we use a nonlinear
mathematical model representing the course of an influen
191 s, albeit within their biological range, the
mathematical model reproduced the different disease cour
192 patial diffusion of fire, our spatiotemporal
mathematical model reproduces these patterns.
193 Mathematical modeling reveals that long-term immunologic
194 Mathematical modelling reveals that a bistable switch, c
195 Moreover,
mathematical modeling showed that an optimal amount of b
196 research in social psychology, we develop a
mathematical model showing how conditioning cooperation
197 Our
mathematical model shows excellent agreement with experi
198 Mathematical model simulations predicted that small pert
199 Using a combination of
mathematical modelling,
statistical simulation and large
200 nal, 22 qualitative, two mixed methods, four
mathematical modelling studies, and no randomised contro
201 We identified eight
mathematical modelling studies; the state of the literat
202 A
mathematical model successfully reproduces all of the ob
203 Further experiments and
mathematical modeling suggest that varied competition be
204 Mathematical modeling suggests that for the CRISPR ChaCh
205 Mathematical modeling suggests, and experiments confirm,
206 Mathematical modelling suggests that faster dopamine-ind
207 Scientists have introduced
mathematical modeling techniques to predict the release
208 across very large genomic distances using a
mathematical model termed SLICE (statistical inference o
209 Here we develop a
mathematical model,
termed the Common Base Method, for a
210 We also introduce a
mathematical model that accounts for changes in the elec
211 A
mathematical model that can predict acute intracranial h
212 We developed a
mathematical model that captures the behaviour of the ce
213 We derived a
mathematical model that combines material balances and k
214 attern of cell sizes, we propose a tractable
mathematical model that depends on intercellular transpo
215 Here we introduce a
mathematical model that describes the effects of ribosom
216 developed a pharmacokinetic/pharmacodynamic
mathematical model that identifies in silico the most ef
217 To this end, we have developed a
mathematical model that incorporates various proposed me
218 We present a
mathematical model that quantitatively explains this bip
219 Using an empirically calibrated
mathematical model that simulates the natural history of
220 Here we apply a
mathematical model that uses DRC in multiple pathways to
221 By using a recently developed
mathematical model that uses insulin and C-peptide measu
222 To test this hypothesis, we developed a
mathematical model that was constrained by experimental
223 ur experimental results, we have developed a
mathematical model that well describes the iron redox tr
224 We use
mathematical models that describe both bacterial growth
225 ed from healthy individuals, and to generate
mathematical models that predict cellular sensitivity to
226 Our approach combines field data with
mathematical models:
the models separate changes in rela
227 We designed a
mathematical model to correlate the time constant of flu
228 We applied a
mathematical model to data from experimental column stud
229 Accordingly, we developed a
mathematical model to describe the dynamic coupling of i
230 To explore this concern, we develop a
mathematical model to estimate tolerable rates of homing
231 We developed a
mathematical model to evaluate the added benefit of an H
232 We develop a general
mathematical model to examine shape changes in a permeab
233 We developed a
mathematical model to explore the potential for RDT-led
234 We incorporated these relationships in a
mathematical model to guide collection and ordering stra
235 n mixed, so we develop a heuristic strategic
mathematical model to obtain general conclusions about t
236 The goal of this work was to develop a
mathematical model to predict Kaplan-Meier survival curv
237 We used a
mathematical model to predict the direct and indirect ef
238 We used a
mathematical model to project cumulative CVD incidence.
239 o identify all studies that used an original
mathematical model to quantify the impact of a vaccine o
240 We employed a
mathematical model to reveal the penetration depth of se
241 ially explicit, stochastic, individual-based
mathematical model to simulate each gene drive approach
242 We developed a
mathematical model to simulate the lifetime course of PB
243 We developed a deterministic
mathematical model to simulate the mortality trends that
244 In this paper we provide a
mathematical model to study online social debates and th
245 Here we propose a
mathematical model to study the coevolutionary dynamics
246 We subsequently developed a
mathematical model to test the hypothesis that the perce
247 We have developed a
mathematical model to understand the significance of alt
248 We applied
mathematical modeling to Abeta in vivo PET imaging data
249 on surface structuration assay combined with
mathematical modeling to describe the growth of a recons
250 We used
mathematical modeling to determine whether an ionic curr
251 se a combination of single-cell analysis and
mathematical modeling to examine the sources of bimodali
252 Here we use three-dimensional
mathematical modeling to investigate GBM progression and
253 activity with a microfluidic taxis assay and
mathematical modeling to investigate the thermotactic re
254 Here, we have performed
mathematical modeling to provide a quantitative underpin
255 Here we combine experimental embryology and
mathematical modelling to analyse the role of the TGFbet
256 xity of ecosystems has led ecologists to use
mathematical modelling to gain understanding of ecologic
257 We used both statistical methods and dynamic
mathematical models to (i) evaluate the empirical assays
258 ermore they combined in vivo experiments and
mathematical models to describe for the first time in ar
259 ng metabolic labeling/RNA sequencing and new
mathematical models to estimate rates.
260 INTERPRETATION: The application of
mathematical models to existing clinical data allowed es
261 Rates were obtained by applying
mathematical models to prostate-specific antigen levels
262 analog cell labeling and developed tailored
mathematical models to quantify cell proliferation and m
263 We developed
mathematical models to study two different mechanisms by
264 variability at the molecular level, to apply
mathematical models to the interpretation of the data an
265 Herein we use
mathematical models to uncover the relative contribution
266 nvasive imaging, 3D-electron microscopy, and
mathematical modelling)
to show that phloem unloading of
267 xG system and the application of theoretical
mathematical models toward an understanding of the syste
268 gy are described, and two different types of
mathematical models used for studying metabolism are dis
269 In this study, we develop an informative
mathematical model using hydantoin derivatives as a trai
270 o this end, we parameterize a well-supported
mathematical model using transient measurements of LacZ
271 A stochastic
mathematical model was adapted for infectious disease tr
272 In summary, a
mathematical model was developed to model tumor growth o
273 A
mathematical model was developed to represent HIV transm
274 and iPSC colony formation quantitatively, a
mathematical model was developed to statistically predic
275 The
mathematical model was experimentally validated by emplo
276 t-therapy for 14 days and a high-dimensional
mathematical model was fit to the data.
277 Mathematical modelling was used to create regulatory net
278 With the aid of a heuristic
mathematical model,
we postulate that if the rate of pha
279 With the help of an experimentally validated
mathematical model,
we show that this biphasic control r
280 Using a
mathematical model,
we suggest mechanisms by which patho
281 As predicted by
mathematical modeling,
we confirm that biofilms resolve
282 Using quantitative image processing and
mathematical modeling,
we demonstrate that the resulting
283 ing, and pharmacological tools, validated by
mathematical modeling,
we determined that the functional
284 With the use of
mathematical modeling,
we estimated gastric emptying, gl
285 Combining experiments and
mathematical modeling,
we show that metabolites consumed
286 Fitting
mathematical models,
we estimated that a large fraction
287 rvations and building on ideas from previous
mathematical models,
we present a new, thermodynamically
288 Using
mathematical models,
we show that this increase in perfo
289 process these data and interpret them using
mathematical models,
we use a probabilistic, hierarchica
290 Mathematical models (
Weibull and exponential models) wer
291 olved in laboratory experiments we propose a
mathematical model where the c-di-GMP network is analogo
292 This is consistent with
mathematical models which predict the association of tra
293 Mathematical modeling,
which included the decay kinetics
294 ong the important tools in this approach are
mathematical models,
which can explore probable benefits
295 thesis, we propose a simple non-neuromorphic
mathematical model with a plastic self-organized velocit
296 In this work, we combine
mathematical modeling with experimentation to address th
297 We combined
mathematical modelling with experiments in heart cells f
298 In the present study, we combined
mathematical modelling with information-rich dynamic cla
299 e demonstrate that a combination of explicit
mathematical models with an approximate Bayesian computa
300 ve to develop physiologically representative
mathematical models with which to compare to experimenta