1 much more fruitful approach to understanding
mathematical abilities.
2 n analyzed in detail and currently available
mathematical action-potential (AP) models do not take in
3 confocal and electron microscopy as well as
mathematical analyses, we examined the hydraulic archite
4 Mathematical analysis further shows how these patterns s
5 The study is based on previously reported
mathematical analysis of arterial waveform that extracts
6 Moreover, the
mathematical analysis of how IR affects the nerve could
7 Here we present a
mathematical analysis of the within-host dynamics of pla
8 Here we show using both simulations and
mathematical analysis that not only the rate but the pha
9 ere, we propose a general procedure based on
mathematical analysis that provides an answer to this qu
10 When
mathematical and computational dynamic models reach infi
11 Computational psychiatry aims to apply
mathematical and computational techniques to help improv
12 The authors performed a combined
mathematical and echocardiographic study to understand t
13 as developed for convenience, without formal
mathematical and graphic assessment to validate its suit
14 Our
mathematical and numerical models can be used to predict
15 By applying
mathematical and physical principles to a range of biolo
16 D'Arcy Thompson was a proponent of applying
mathematical and physical principles to biological syste
17 search increasingly relies on computational,
mathematical,
and statistical thinking, supporting the t
18 Here we used an advanced
mathematical approach named topological data analysis (T
19 on the contents of our network, we develop a
mathematical approach to elucidate representative microb
20 on discussed the necessity of a physical and
mathematical approach to understanding the relationship
21 rupture events were corrected by using a new
mathematical approach.
22 Although purely
mathematical approaches exist, they usually rely on the
23 The procedure includes two different
mathematical approaches to describe and reproduce the di
24 logy and immunology; ecology, evolution, and
mathematical biology; functional and comparative OMICs;
25 al substrate concentration, and we present a
mathematical bound, in terms of external 1,2-propanediol
26 s as a foundation not only for numerical and
mathematical cognition, but also for decision making.
27 The
mathematical concept of topology has brought about signi
28 d different subjects, using virtual and real
mathematical concepts simulated by pictures.
29 s engage children's spontaneous, nonsymbolic
mathematical concepts.
30 ctional process between picture language and
mathematical concepts: abstraction and simulation.
31 allowed access to a considerably simplified
mathematical correlation of substrate and catalyst struc
32 he idea lay dormant, regarded primarily as a
mathematical curiosity.
33 The
mathematical deconvolution method was successfully appli
34 lid tumour from bulk gene expression data by
mathematical deconvolution, using indication-specific an
35 e propose a mean-field model that provides a
mathematical description for the observed trend.
36 ny cases they require minimal coding, just a
mathematical description of the desired function.
37 A
mathematical description was obtained via a road-map inv
38 cle spacing can be recapitulated by specific
mathematical equations in embryos and larvae and that ac
39 ithout needing to go through the complicated
mathematical equations.
40 A
mathematical equivalence between bilayers and curved mon
41 We then developed, to our knowledge, a new
mathematical estimate for the resolution in localization
42 To the best of our knowledge, the
mathematical expression for the capacity limit of FTN no
43 The
mathematical expression shows that FTN NOFDM signal has
44 of new ideas, such as one finds when simple
mathematical expressions can describe a problem.
45 in core-shell structure of Au279 follows the
mathematical formula for magic number shells: Au@Au12@Au
46 While TDA rests on strong
mathematical foundations from topology, in applications,
47 We develop a general
mathematical framework based on instantaneous transforma
48 Here we develop a common
mathematical framework for understanding the relationshi
49 A
mathematical framework is devised to allow the efficacy
50 all of these cases by developing a unifying
mathematical framework that characterizes all of these e
51 Here we present a general
mathematical framework that provides a unifying umbrella
52 Here, we show that variations in the
mathematical functions currently used to simulate temper
53 Here, we present the
mathematical implementation of a tomographic algorithm,
54 Here, we explore the conceptual and
mathematical ingredients required for an exact treatment
55 lar methodology, which is however plagued by
mathematical intractability.
56 rized a new alignment free method based on a
mathematical kernel for scoring the similarity of protei
57 hese approaches are variations of a unifying
mathematical machinery - network propagation - suggestin
58 A
mathematical method is presented that allows deconvoluti
59 e of tomography remains the same, that is, a
mathematical method must be implemented to reconstruct t
60 Here, the authors use a
mathematical model and field data from a seasonally stra
61 The
mathematical model applied here accounts for transport o
62 Here we present a theoretical and
mathematical model based on an extension of evolutionary
63 We build a
mathematical model based on these data and in the aggreg
64 one network designed with the aid of a novel
mathematical model can substantially reduce the AED deli
65 t a drone network designed with the aid of a
mathematical model combining both optimization and queui
66 A
mathematical model describing the decline in volatile co
67 hese factors were correlated in a predictive
mathematical model designed to guide prognosis on the ba
68 We developed a novel
mathematical model explicitly considering the heterogene
69 rimental data for a sample population, and a
mathematical model fit to aggregate data from that sampl
70 This article describes the
mathematical model for an immunochromatographic assay fo
71 ulture, there is not a standard broadly used
mathematical model for bacterial populations growing in
72 A
mathematical model for calculating fluorophore ORF and s
73 , our experimental data, when coupled with a
mathematical model for collective migration, shows that
74 The results were incorporated into a
mathematical model for FMD, in a cattle herd, to evaluat
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 We have developed and applied a novel
mathematical model for SPR data treatment that enables d
78 We developed a climate-driven R0
mathematical model for the transmission risk of Zika vir
79 nventional clinical instruments to develop a
mathematical model guided by cellular mechanisms that qu
80 pact of such dynamical trade-offs by a novel
mathematical model incorporating de novo mutations for b
81 We use a
mathematical model incorporating effects of light, circa
82 Furthermore, a
mathematical model is constructed for the simulation of
83 Here, a computational and
mathematical model is provided to test whether passive m
84 KEY POINTS: A
mathematical model of a small conductance Ca(2)(+) -acti
85 n metabolism and breast cancer, a predictive
mathematical model of an expanded iron homeostasis pathw
86 present, to our knowledge, a new multiscale
mathematical model of arterial contractility accounting
87 Results were interpreted using a
mathematical model of binding-diffusion mediated arteria
88 From these metrics, we developed a
mathematical model of cancer biomarker kinetics that acc
89 Indeed, our biphasic
mathematical model of Cdc42 polarization predicts that p
90 The present paper develops a
mathematical model of CP based on a dynamic network that
91 These results were validated using a
mathematical model of CSNs, including IKD and TRPM8, sho
92 With a network-based
mathematical model of HIV, Neisseria gonorrhoeae (NG), a
93 hat the bifurcation properties of a standard
mathematical model of lateral inhibition can lead to sta
94 A
mathematical model of measles transmission and vaccine s
95 Here we present a
mathematical model of neutrophil signal relay that focus
96 A
mathematical model of phagocytosis suggests that hFcgamm
97 METHODS AND We combined an established
mathematical model of Plasmodium falciparum transmission
98 We use a
mathematical model of smallholders' fields to determine
99 To investigate this, we developed a
mathematical model of the adrenal steroidogenic regulato
100 This observation formed the basis for a new
mathematical model of the BG, quantitatively fitted to t
101 A
mathematical model of the circadian pacemaker and its re
102 re we construct and analyze a coarse-grained
mathematical model of the fission yeast ring to explore
103 We develop a
mathematical model of the function of the 1,2-propanedio
104 d that might integrate these findings with a
mathematical model of the interpersonal influence system
105 ata informed changes in our well-established
mathematical model of the rabbit myocyte.
106 transformation-specific factors to develop a
mathematical model of Yan occupancy at chemical equilibr
107 in line with experimental observations, the
mathematical model predicted a significantly higher half
108 A
mathematical model predicts that colonies formed solely
109 cally motivated, control strategies, using a
mathematical model previously fitted to the spread of ci
110 s work we derive, to our knowledge, a new 1D
mathematical model quantifying canal biomechanics based
111 In the present work, we use a nonlinear
mathematical model representing the course of an influen
112 s, albeit within their biological range, the
mathematical model reproduced the different disease cour
113 research in social psychology, we develop a
mathematical model showing how conditioning cooperation
114 Our
mathematical model shows excellent agreement with experi
115 Mathematical model simulations predicted that small pert
116 A
mathematical model successfully reproduces all of the ob
117 We also introduce a
mathematical model that accounts for changes in the elec
118 A
mathematical model that can predict acute intracranial h
119 We developed a
mathematical model that captures the behaviour of the ce
120 We derived a
mathematical model that combines material balances and k
121 attern of cell sizes, we propose a tractable
mathematical model that depends on intercellular transpo
122 Here we introduce a
mathematical model that describes the effects of ribosom
123 developed a pharmacokinetic/pharmacodynamic
mathematical model that identifies in silico the most ef
124 To this end, we have developed a
mathematical model that incorporates various proposed me
125 We present a
mathematical model that quantitatively explains this bip
126 Using an empirically calibrated
mathematical model that simulates the natural history of
127 Here we apply a
mathematical model that uses DRC in multiple pathways to
128 By using a recently developed
mathematical model that uses insulin and C-peptide measu
129 We designed a
mathematical model to correlate the time constant of flu
130 Accordingly, we developed a
mathematical model to describe the dynamic coupling of i
131 We developed a
mathematical model to evaluate the added benefit of an H
132 We incorporated these relationships in a
mathematical model to guide collection and ordering stra
133 n mixed, so we develop a heuristic strategic
mathematical model to obtain general conclusions about t
134 The goal of this work was to develop a
mathematical model to predict Kaplan-Meier survival curv
135 We used a
mathematical model to predict the direct and indirect ef
136 We employed a
mathematical model to reveal the penetration depth of se
137 ially explicit, stochastic, individual-based
mathematical model to simulate each gene drive approach
138 In this paper we provide a
mathematical model to study online social debates and th
139 Here we propose a
mathematical model to study the coevolutionary dynamics
140 We subsequently developed a
mathematical model to test the hypothesis that the perce
141 We have developed a
mathematical model to understand the significance of alt
142 In this study, we develop an informative
mathematical model using hydantoin derivatives as a trai
143 o this end, we parameterize a well-supported
mathematical model using transient measurements of LacZ
144 A stochastic
mathematical model was adapted for infectious disease tr
145 In summary, a
mathematical model was developed to model tumor growth o
146 A
mathematical model was developed to represent HIV transm
147 and iPSC colony formation quantitatively, a
mathematical model was developed to statistically predic
148 The
mathematical model was experimentally validated by emplo
149 t-therapy for 14 days and a high-dimensional
mathematical model was fit to the data.
150 olved in laboratory experiments we propose a
mathematical model where the c-di-GMP network is analogo
151 Using a
mathematical model, closely tied to experimental work, w
152 Additionally, we developed a
mathematical model, parameterized by cell viability expe
153 Here we develop a
mathematical model, termed the Common Base Method, for a
154 With the aid of a heuristic
mathematical model, we postulate that if the rate of pha
155 Using a
mathematical model, we suggest mechanisms by which patho
156 utant embryos and combined these data with a
mathematical model-based computational screen to test hy
157 involvement supports a previously published
mathematical model.
158 accompanying polysaccharide synthesis with a
mathematical model.
159 ssure generation with a previously validated
mathematical model.
160 us to construct an improved, more predictive
mathematical model.
161 ate the formation of demarcation line with a
mathematical model.
162 us virus, we incorporated this effect into a
mathematical model.
163 Specifically, through
mathematical modeling and experimental validation, we id
164 Prominent among them are
mathematical modeling and laboratory experiments that co
165 ally analyzes the latest developments in the
mathematical modeling and simulation techniques that hav
166 We explored, through
mathematical modeling and simulations, the size of poten
167 Previous
mathematical modeling approaches demonstrated that diffe
168 We used
mathematical modeling as a theoretical framework to brid
169 Mathematical modeling demonstrated that lower CAR sensit
170 However, decades-old experimental work and
mathematical modeling document methods to calculate both
171 ve experimental data, force measurements and
mathematical modeling has changed our understanding of m
172 Previous
mathematical modeling has suggested that the morphology
173 Mathematical modeling highlights the role of these three
174 Here, we examine by means of
mathematical modeling how this interaction influences se
175 Mathematical modeling indicates that accentuated costs t
176 Integration of experiments and
mathematical modeling indicates that extracellular potas
177 olecular biology, computational biology, and
mathematical modeling is an efficient approach to identi
178 We combine
mathematical modeling of genome evolution with comparati
179 Flow cytometric assessment and
mathematical modeling of intraerythrocytic parasite deve
180 Overall, our data support the use of
mathematical modeling of intratumoral Darwinian interact
181 In conclusion, using
mathematical modeling of published and newly generated d
182 Unfortunately, standard
mathematical modeling practices mask the importance of p
183 Mathematical modeling predicts that dependence of signal
184 Our
mathematical modeling proposes that the observed spectra
185 Mathematical modeling provided estimates of receptor agg
186 Mathematical modeling reveals that long-term immunologic
187 Further experiments and
mathematical modeling suggest that varied competition be
188 Mathematical modeling suggests that for the CRISPR ChaCh
189 Mathematical modeling suggests, and experiments confirm,
190 Scientists have introduced
mathematical modeling techniques to predict the release
191 We used
mathematical modeling to determine whether an ionic curr
192 se a combination of single-cell analysis and
mathematical modeling to examine the sources of bimodali
193 Here we use three-dimensional
mathematical modeling to investigate GBM progression and
194 activity with a microfluidic taxis assay and
mathematical modeling to investigate the thermotactic re
195 Here, we have performed
mathematical modeling to provide a quantitative underpin
196 d bed of identical grains using simulations,
mathematical modeling, and experiments.
197 c techniques, quantitative cell imaging, and
mathematical modeling, our study in Caulobacter crescent
198 As predicted by
mathematical modeling, we confirm that biofilms resolve
199 Using quantitative image processing and
mathematical modeling, we demonstrate that the resulting
200 ing, and pharmacological tools, validated by
mathematical modeling, we determined that the functional
201 Combining experiments and
mathematical modeling, we show that metabolites consumed
202 Mathematical modeling, which included the decay kinetics
203 nation of kinetic parameters and data-driven
mathematical modelling allowed us to obtain detailed inf
204 Here we use a joint
mathematical modelling and experimental approach to asse
205 Here we combine
mathematical modelling and lab experimentation to invest
206 is to highlight emerging concepts, including
mathematical modelling and the molecular engineering of
207 We use a
mathematical modelling approach to estimate the impact o
208 ot intuitive, exemplifying the importance of
mathematical modelling approaches.
209 Mathematical modelling has become an established tool fo
210 High-throughput sequencing and
mathematical modelling have yielded detailed genome-wide
211 Mathematical modelling indicates that tumour spatial str
212 In this study, we consider randomness in the
mathematical modelling of forest trees by incorporating
213 Mathematical modelling predicted that ecDNA amplificatio
214 Mathematical modelling predicted that tubular Na(+) reab
215 Mathematical modelling predicted that tubular Na(+) reab
216 nal, 22 qualitative, two mixed methods, four
mathematical modelling studies, and no randomised contro
217 Mathematical modelling suggests that faster dopamine-ind
218 xity of ecosystems has led ecologists to use
mathematical modelling to gain understanding of ecologic
219 Mathematical modelling was used to create regulatory net
220 We combined
mathematical modelling with experiments in heart cells f
221 nvasive imaging, 3D-electron microscopy, and
mathematical modelling) to show that phloem unloading of
222 Using a combination of
mathematical modelling, statistical simulation and large
223 icine tools-such as genomics, radiomics, and
mathematical modelling-could open new doors to personali
224 vaccination programmes is routinely based on
mathematical modelling.
225 normal control tissues (aorta, psoas) and in
mathematical models (P < 0.01).
226 Mathematical models (Weibull and exponential models) wer
227 Mathematical models accounting for this heterogeneity de
228 Mathematical models and experimental insights rationaliz
229 Here, we formalized these theories into
mathematical models and performed biological experiments
230 Mathematical models are excellent tools to meet this dem
231 onitored on a large scale through the use of
mathematical models by way of differential equations, fo
232 whether the inclusion of humidity forcing in
mathematical models describing influenza transmission im
233 reactions; it is therefore necessary to use
mathematical models for holistic studies.
234 lp overcome this complexity, systems biology
mathematical models have been generated for predicting b
235 The use of
mathematical models in biology is referred to as systems
236 More specifically, we developed
mathematical models of acquired and inherited long-QT sy
237 Mathematical models of emergent pathogens allow forecast
238 Complex
mathematical models of interaction networks are routinel
239 ness and cognitive impairments, but existing
mathematical models of sleep and cognitive performance d
240 Most conceptual and
mathematical models of soil vapor intrusion assume that
241 Here we develop
mathematical models of Tfh cells in germinal centers to
242 Mathematical models of the dynamics of a drug within the
243 Mathematical models of the response of zeaxanthin- and l
244 surement and treatment, difficult-to-compare
mathematical models of underlying mechanisms, and unknow
245 We developed
mathematical models of viral dynamics upon initial oral
246 Finally, we demonstrate that when leading
mathematical models of working memory are adjusted to ac
247 equiring pure compound synthesis, or complex
mathematical models or in-silico simulations.
248 The
mathematical models presented can explain a number of pr
249 ed from healthy individuals, and to generate
mathematical models that predict cellular sensitivity to
250 We used both statistical methods and dynamic
mathematical models to (i) evaluate the empirical assays
251 ermore they combined in vivo experiments and
mathematical models to describe for the first time in ar
252 ng metabolic labeling/RNA sequencing and new
mathematical models to estimate rates.
253 Rates were obtained by applying
mathematical models to prostate-specific antigen levels
254 analog cell labeling and developed tailored
mathematical models to quantify cell proliferation and m
255 We developed
mathematical models to study two different mechanisms by
256 Herein we use
mathematical models to uncover the relative contribution
257 xG system and the application of theoretical
mathematical models toward an understanding of the syste
258 gy are described, and two different types of
mathematical models used for studying metabolism are dis
259 e demonstrate that a combination of explicit
mathematical models with an approximate Bayesian computa
260 ve to develop physiologically representative
mathematical models with which to compare to experimenta
261 ng, qPCR and experimental xenodiagnoses with
mathematical models, Doehl et al. argue that the patchy
262 Current
mathematical models, however, do not fully address the p
263 Using
mathematical models, we show that this increase in perfo
264 process these data and interpret them using
mathematical models, we use a probabilistic, hierarchica
265 ms, we developed three biologically anchored
mathematical models: 1) parallel activation of Fshb inhi
266 Our approach combines field data with
mathematical models: the models separate changes in rela
267 A recent paper by Karin et al. introduced a
mathematical notion called dynamical compensation (DC) o
268 We use
mathematical,
numerical, and empirical approaches to sho
269 The Fourier transform is a ubiquitous
mathematical operation which arises naturally in optics.
270 area has seen some successes in identifying
mathematical operations for which quantum algorithms off
271 The unique correspondence between
mathematical operators and photonic elements in wave opt
272 A
mathematical population-genetics model showed how tolera
273 sient infections to occur, we identified two
mathematical prerequisites: a very small number of initi
274 Hence, the fundamental
mathematical principle of synchronization through instan
275 sed and model-based methods that draw on the
mathematical principles of dynamical systems.
276 Deconvolution is a
mathematical process of resolving an observed function i
277 easily calculable and has several desirable
mathematical properties.
278 e monkey and using computational models from
mathematical psychology to relate these neural data to b
279 We provide a
mathematical rationale, and then demonstrate it experime
280 stimulus value, follow a surprisingly simple
mathematical relation.
281 itionally, those studies that determined the
mathematical relationship between visual field sensitivi
282 Mathematical results are known for special structures in
283 Using a
mathematical simulation, we project the 5- and 20-year c
284 Mathematical simulations indicate that the addition of m
285 ted the high-resolution anatomical data into
mathematical simulations of cardiac electrical depolaris
286 Mathematical simulations showed that hypoglycemia would
287 tome profiling, functional perturbations and
mathematical simulations, we find that mesenchyme-derive
288 dren also showed immediate gains on symbolic
mathematical skills but displayed no advantage in subseq
289 odern synthesis in biology will be driven by
mathematical,
statistical, and computational methods bei
290 A variation graph is a
mathematical structure that can encode arbitrarily compl
291 Riborex shares a similar
mathematical structure with existing methods, but has a
292 This work presents a
mathematical study of tissue dynamics.
293 vances in instrumentation, computational and
mathematical techniques, this technology has now been ap
294 e that such a transition can be described in
mathematical terms as a sequence of bifurcations that th
295 of RNA-seq data (and are powered by a mature
mathematical theory), or count-based models, which repre
296 Transformation optics, as the underlying
mathematical tool, has proven to be a versatile approach
297 This work thus provides valuable
mathematical tools for interpreting and extracting learn
298 In pursuit of
mathematical tractability, these models use simplified d
299 plications where low computational costs and
mathematical transparency are needed, (2) that more comp
300 We propose a
mathematical Turing model that defines conditions for ex