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1 ays represented a computational challenge in System Biology.
2  broadly applicable across developmental and systems biology.
3 n profiles is still an enormous challenge in systems biology.
4 nk between evolution, molecular biology, and systems biology.
5 aluable resource for genetics, genomics, and systems biology.
6 tructured framework represent a challenge in systems biology.
7 iles has been one of the grand challenges in systems biology.
8 ny fields, including biomedical research and systems biology.
9 ion is a fundamental problem in evolutionary systems biology.
10 s via signal transduction is a core focus in systems biology.
11 m insufficient understanding of the strain's systems biology.
12 ecome a part of the routine data analysis in systems biology.
13 ematical models in biology is referred to as systems biology.
14 ive and an ongoing challenge in the field of systems biology.
15 teractions constitutes a major bottleneck in systems biology.
16 y, medical informatics, cancer genomics, and systems biology.
17 etworks are routinely used for prediction in systems biology.
18 rocesses, as well as cell-scale processes in systems biology.
19 -throughput data is a challenging problem in systems biology.
20 ways and their crosstalk is a cornerstone of systems biology.
21           Networks have become ubiquitous in systems biology.
22 on in silico, with promising applications in systems biology.
23 sion and interaction data is a major goal of systems biology.
24 of scientific exploration at the frontier of systems biology.
25 modeling and analysis techniques employed in systems biology.
26  interactions (PPIs) is a central problem in systems biology.
27 on prospective prediction using the tools of systems biology.
28 bi and NYU New York Centers for Genomics and Systems Biology.
29 ing data into informational networks used in systems biology.
30 isualization library particularly suited for systems biology.
31 Ns) is an important but difficult problem in systems biology.
32 chemistry, molecular genetics, genomics, and systems biology.
33 d on developmental biology and computational systems biology.
34 ugh applying these techniques to omics data, systems biology addresses the problems posed by the comp
35                                       Cancer systems biology aims to understand cancer as an integrat
36 , and DLBCL patient serum samples leveraging systems biology analyses and droplet digital PCR (ddPCR)
37                   Subsequent experiments and systems biology analyses confirm this prediction, and su
38                                              Systems biology analyses demonstrated that inflammatory
39                                              Systems biology analyses highlight both similarities and
40                                              Systems biology analyses identified multiple functional
41 ntellectual disability and CHD by conducting systems biology analyses of genes prioritized by mTADA.
42 rchers to study cellular senescence, and our systems biology analyses reveal new insights and gene re
43 entified from large-scale bioinformatics and systems biology analyses.
44                                              Systems biology analysis of 110 proteins with Benjamini-
45                                   Integrated systems biology analysis of transcriptomic, proteomic an
46                                              Systems biology analysis relating to cell behaviors and
47                                  RNA-seq and systems biology analysis revealed a striking sexual dimo
48 ene expression studies in conjunction with a systems biology analysis.
49  reveal these causes, we used a multi-omics, systems biology analytical approach using biomedical pro
50 to overcome target-based bottlenecks through systems biology analytics, such as protein-protein inter
51                           The combination of systems biology and bioinformatics approaches, together
52 g genomics, molecular biology, biochemistry, systems biology and bioinformatics.
53  basic research, genome analysis, modelling, systems biology and education.
54 uracy on numeric and real data examples from systems biology and epidemiology.
55 nvaluable for our understanding of molecular systems biology and for characterizing novel gene functi
56  advances in the fields of computational and systems biology and highlight opportunities for research
57 glected diseases, especially in the areas of systems biology and immunology; ecology, evolution, and
58                                              Systems biology and innovative data integration can prov
59 pics in bioinformatics, medical informatics, systems biology and intelligent computing.
60 ted dimensionality will catalyze advances in systems biology and medical diagnostics.
61 odels (GSMMs) are increasingly important for systems biology and metabolic engineering research as th
62 ill be of great use to the wider biological, systems biology and modelling communities.
63 existing knowledge of COPD pathobiology, how systems biology and network medicine can improve underst
64 formation that existing technology provides (systems biology and network medicine) so diagnosis, stra
65  use of large linear and nonlinear models in systems biology and other applications involving multisc
66                                              Systems biology and synthetic biology are increasingly u
67 ynamics has been one of the core subjects in systems biology, and is the focus of this study.
68 egrated shotgun redox proteomics, structural systems biology, and machine learning to resolve propert
69 he perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas
70         Metabolomics plays a pivotal role in systems biology, and NMR is a central tool with high pre
71 tion, gene regulatory networks, modeling and systems biology, and synthetic biology.
72 advances in genomics, molecular biology, and systems biology, and will continue to accelerate as acce
73 investigators to develop their own in silico systems biology applications.
74 exist, but have so far rarely been tested in systems biology applications.
75                                      Using a system biology approach and functional studies, we demon
76 ought stress in sunflower plants, by using a system biology approach.
77 se-related peripheral immune signatures in a systems biology approach covering a broad range of adapt
78        We therefore developed InFlo, a novel systems biology approach for characterizing complex biol
79 ate tumor growth and provides a framework of systems biology approach in studying tumor-related immun
80                          Walsh et al. took a systems biology approach integrating computational, in v
81                             Moreover, such a systems biology approach may enable restoration of the p
82 entering the era of personalized medicine, a systems biology approach merging the numerous clinical p
83                                          Our systems biology approach offers a possible explanation f
84 ly SIV infected AGMs and RMs, we developed a systems biology approach termed Conserved Gene Signature
85                           Here, we present a systems biology approach that combines transcriptomic an
86                   Metabolomics is a powerful systems biology approach that monitors changes in biomol
87 effort and propose research priorities for a systems biology approach to CF lung disease.
88                              Here, we used a systems biology approach to characterize the temperature
89  study, the authors use for the first time a systems biology approach to comprehensively evaluate cli
90                               Here, we use a systems biology approach to construct a mathematical mod
91 ators of the immune system, and so we used a systems biology approach to construct an miRNA regulator
92                           Here we utilized a systems biology approach to decipher the regulatory prin
93                               Here, we use a systems biology approach to define the contributions of
94                                We employed a systems biology approach to delineate upper-airway gene
95                      We therefore utilized a systems biology approach to elucidate how UBE3A loss imp
96                 Here, we apply a multistage, systems biology approach to elucidate the disease mechan
97                           Here, we applied a systems biology approach to gain deeper insights into th
98 sults support the usefulness of integrative, systems biology approach to gain insights into complex n
99                                    We used a systems biology approach to identify host transcriptiona
100         Here, we delineate a framework for a systems biology approach to infectious disease in three
101                            Here, we employ a systems biology approach to model auxin transport based
102                                      Using a systems biology approach to prioritize potential points
103                           Here, we applied a systems biology approach to study immune responses in su
104                                            A systems biology approach was developed in tomato (Solanu
105                   Here, a novel multi-tiered systems biology approach was used to predict metabolites
106                 To address this challenge, a systems biology approach was used.
107     To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean m
108  multi-cellular systems using an integrative systems biology approach, better understanding of protei
109 esenchymal subtype of ovarian cancer using a systems biology approach, involving a variety of molecul
110 oRNA-124 (miR-124), determined with a tiered systems biology approach, is responsible for increased e
111                                  Recently, a systems biology approach, using omics datasets, has reve
112                         Using an integrative systems biology approach, we also revealed that M2 polar
113                          Using a data-driven systems biology approach, we built a MB-specific interac
114                         Using an integrative systems biology approach, we identified signals of treat
115                                      Using a systems biology approach, we identify a new network of z
116                                      Using a systems biology approach, we interrogated the AR-regulat
117 r a combination of three common POPs using a systems biology approach, which may link POP exposure to
118 ticosteroid response in asthma using a novel systems biology approach.
119 on sources was analysed, using an integrated systems biology approach.
120  cell biology, and computational biology - a systems biology approach.
121                  Here we applied an unbiased systems-biology approach to explore the cellular specifi
122     We thus finally discuss the potential of systems-biology approach to predict its occurrence and t
123          In our view, these should emphasize system biology approaches that integrate omic, pharmacol
124                We conclude by discussing how systems biology approaches are a fruitful avenue for add
125                                              Systems biology approaches are establishing the links be
126        In this Analysis, we survey six major systems biology approaches for mapping and modelling can
127 ell as in integrative analytical strategies, systems biology approaches for the study of infectious d
128           Combining integrative genomics and systems biology approaches has revealed new and conserve
129 cent advances of multiomics technologies and systems biology approaches have generated large-scale he
130                           Bioinformatics and systems biology approaches identified potential pathways
131                                              Systems biology approaches identify numerous master regu
132              In parallel, bioinformatics and systems biology approaches including genomic analysis, c
133 l cell biology remain relatively unexplored, systems biology approaches like mass spectrometry (MS) b
134 es, cell types, and organ systems, rendering systems biology approaches particularly amenable to thei
135                                              Systems biology approaches relying on gene ontologies, g
136 oaches that identify key organism traits and systems biology approaches that integrate traditional ph
137 iple model is an important step in employing systems biology approaches to analyze an intracellular s
138 rgets; and (4) to further the development of systems biology approaches to decipher the molecular mec
139                                      We used systems biology approaches to explore the alternative hy
140                                       We use systems biology approaches to identify a unique IPF prot
141 e performed RNA-sequencing analyses and used systems biology approaches to identify pathways that are
142 ing hepatocytes, we applied state-of-the-art systems biology approaches to models of liver regenerati
143  validation must still accompany these novel systems biology approaches to realize their full potenti
144    In this Pulmonary Perspective, we discuss systems biology approaches, especially but not limited t
145 grating specialized shear-stress models with systems biology approaches, including transcriptome, met
146                                         With systems biology approaches, interventions can be tailore
147 nt of biomarkers of BBB integrity along with systems biology approaches, should enable new personaliz
148 metabolic modeling and other nowadays common systems biology approaches-allowed them to anticipate th
149  serial integrated metabolomic and proteomic systems biology approaches.
150 ia has not been characterized extensively by systems biology approaches.
151     These data were deconvoluted using three systems biology approaches: "Orbital-deconvolution" eluc
152  challenges and opportunities in translating systems-biology approaches from cultured cells to living
153                                              Systems-biology approaches in immunology take various fo
154                           Recent advances in systems biology are changing what is possible, however,
155            In this review, the principles of systems biology are described, and two different types o
156 us, emerging tools in big data analytics and systems biology are facilitating novel insights on glyca
157  metagenomics, proteomics, metabolomics, and systems biology are providing a new emphasis in research
158     The present review advocates single cell systems biology as the optimal level of analysis for rem
159 arch, especially the study on organism-level systems biology at multiple levels.
160                                      Using a systems biology-based approach to an assessment of 779 p
161                                            A systems biology-based approach would help to decipher th
162                                              Systems biology-based approaches can provide an unpreced
163 roarray measurements forms a core element of systems biology-based phenotyping.
164 enome annotation, genome analysis, modeling, systems biology, basic research and education.
165 edicine) have the potential to revolutionize systems biology by enabling researchers to study interac
166 oncept of network motifs was introduced into Systems Biology by Milo, Alon and colleagues in 2002, qu
167                                  Advances in systems biology can be exploited to comprehensively unde
168      Finally, the ways that quantitative and systems biology can help shed light on the plethora of o
169                                              Systems biology can unravel complex biology but has not
170 d pharmacological screens with an integrated systems-biology characterization.
171 oles of quantitative proteomics in molecular systems biology, clinical research and personalized medi
172 the key motivation behind recent worksin the systems biology community to employDNNs to solve importa
173 ata, Operating procedures and Models for the Systems Biology community.
174 alance analysis (FBA), has become a standard systems-biology computational method to study cellular m
175 istic approach that integrates synthetic and systems biology concepts to achieve outcomes not possibl
176                                          Our systems biology data analysis, in combination with real-
177 tegrative analysis of experimental molecular systems biology data and quantitative prediction of phys
178                                   Integrated systems biology-directed analyses of these data layers a
179 , immunology, metabolism, endocrinology, and systems biology discussed genetic and environmental dete
180 eflecting the common belief that cancer is a systems biology disease.
181 , evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental b
182 ts that enabled genome-scale investigations, systems biology emerged as a field aiming to understand
183          We thus demonstrate that structural systems biology enables a proteome-wide, computational a
184                  Finally, the application of systems biology for analyzing global regulatory structur
185 Approach in a Minority Community Integrating Systems-Biology for Promotion of Health [FAMILIA]; NCT02
186 Approach in a Minority Community Integrating Systems-Biology for Promotion of Health) study is a clus
187                          Here we present the System Biology Format Converter (SBFC), which provide a
188 gration of experimentally verified data with system biology framework extracts the miRNA network for
189 individual enzymatic components, is to use a systems biology framework, such as a Genome-Scale Metabo
190 e two leads to the formation of a structural systems biology framework, which we have used to analyze
191 red five novel plant defense players using a systems biology-fueled top-to-bottom approach and demons
192 directing towards biological methods such as systems biology, genetic engineering and bio-refining fo
193 at differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards.
194  mathematical models were produced using the Systems Biology Graphical Notation and Systems Biology M
195                                 The field of systems biology has been rapidly developing in the past
196                                              Systems biology has been used to examine a range of micr
197              In turn, multitissue multiomics systems biology has emerged to comprehensively elucidate
198                                              Systems biology has matured as a discipline, and its met
199                                  Research in systems biology has taken advantage of these opportuniti
200                     Polyomics, big data, and systems biology have demonstrated a profound complexity
201 merous approaches in functional genomics and systems biology have led to a greater understanding of p
202 ovative technologies, such as proteomics and systems biology, help to advance this research field and
203                                     Finally, systems biology identified unique metabolic versatility
204 ed investigation into the role of glymphatic system biology in AD and iNPH models could lead to new s
205 contend that such successful applications of systems biology in elucidating the functional architectu
206  we offer our viewpoint of past successes of systems biology in elucidating the otherwise hidden acti
207                      The growing interest in systems biology in executable models and their analysis
208                                 The power of systems biology in retrieving novel insights and formula
209                      We have developed a new systems-biology-informed deep learning algorithm that in
210                              We also discuss systems biology insights gleaned from the recent advance
211 tocols, interlink them in the context of the systems biology investigations that produced them, and t
212                                              Systems biology is increasingly being applied in nanosaf
213                         A grand challenge of systems biology is to predict the kinetic responses of l
214     An important and yet challenging task in systems biology is to reconstruct cellular signaling sys
215                  One of the central tasks in systems biology is to understand how cells regulate thei
216                     The goal of genomics and systems biology is to understand how complex systems of
217                         A key goal of cancer systems biology is to use big data to elucidate the mole
218                                           In systems biology, it is of great interest to identify pre
219 w research tool in trauma by using metabolic systems biology, laying the foundation for personalized
220 col offers the ability to study tissues at a systems biology level and directly linking results to ti
221 es our understanding of pathogenicity at the systems biology level and provides enticing prospects fo
222                                              Systems biology maps also identify previously underappre
223                          Our sample of 2,070 systems biology maps captures all literature-curated can
224  Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qua
225                 A community standard such as Systems Biology Markup Language (SBML) can serve as a ne
226                        The input is based on systems biology markup language (SBML) format, which is
227  how query results are converted back to the Systems Biology Markup Language (SBML) standard format.
228  on system behaviour for models specified in Systems Biology Markup Language (SBML).
229          Any genome-scale model based on the Systems Biology Markup Language can be uploaded to the t
230 h and retrieval of parameter values from the Systems Biology Markup Language models stored in BioMode
231 g the Systems Biology Graphical Notation and Systems Biology Markup Language, respectively.
232            To help overcome this complexity, systems biology mathematical models have been generated
233 tors, some questions are best addressed with systems biology mathematical models.
234                 Integrating epigenetics into systems biology may critically enhance research on psych
235          This knowledge can be obtained with systems biology/medicine approaches that account for the
236                    Here we use a data-driven systems biology meta-analytical approach across three hu
237                                        Here, systems biology method of dynamics correlation network b
238 as a fertile platform for the application of systems biology methodologies in combination with tradit
239               Here, we build on our previous systems biology model of VEGF transport and kinetics in
240 h to infer the structure and parameters of a systems biology model.
241 s a theoretical foundation for circuit-based systems biology modeling.
242 nable biological insights through optimizing systems biology modeling.
243 ls Parameters will be a valuable service for systems biology modellers.
244                                              Systems biology models are often characterised as either
245                                              Systems biology models are used to understand complex bi
246     One of the major bottlenecks in building systems biology models is identification and estimation
247                                              Systems Biology models reveal relationships between sign
248 f simplifying assumptions is crucial to make systems biology models tractable while still representat
249                        These methods combine systems biology models with population and single-cell q
250 used to perform Bayesian analysis of complex systems biology models.
251 eful to analyse complex and high dimensional Systems Biology models.
252                                In the era of systems biology, multi-target pharmacological strategies
253 nce insights into the structural biology and systems biology of cell signaling.
254 rom DNA, with important implications for the systems biology of gene regulation by Fis.
255 he model provides opportunities to study the systems biology of innate immunity and to determine how
256              Moreover, it contributes to the systems biology of natural variation, as a substantial n
257  particular, we have focussed on analysing a systems biology of the brain using both simulated and me
258         Existing meta-analysis approaches in systems biology often focus on hypothesis testing and ne
259 orts spread across Europe were combined with systems biology (omics, IgE measurement using microarray
260 ferentiation/development, tumorigenesis, and systems biology on a global, genome-wide level.
261  clustering approach taken from genomics and systems biology on two large independent cognitive datas
262 y is the next great chapter in synthetic and systems biology, particularly for microorganisms.
263 approaches for DTI prediction that adopt the systems biology perspective generally exploit the ration
264                         This work provided a systems biology perspective on understanding the antibio
265 harmacokinetics/pharmacodynamics (PK/PD) and systems biology/pharmacology.
266 mational spatial analytics computational and systems biology platform (SpAn) that predicts clinical o
267 on known genetic factors in NAFLD to build a systems biology prediction model that includes functiona
268 s control many biological processes, so that systems biology provides a valuable approach in this fie
269                                       Modern systems biology requires extensive, carefully curated me
270 es a complex immune response that requires a systems biology research approach.
271                   A big challenge in current systems biology research arises when different types of
272 ccessible repository for storing and sharing systems biology research assets.
273 ome these limitations would fill the void in systems biology research, catalyze clinical innovations,
274 ty between formats is a recurring problem in systems biology research.
275 derived biological models and computer-based systems biology simulations.
276 rmulated in terms of a well-known concept in systems biology, statistics, and control theory-that of
277        Our approach promotes a comprehensive systems biology strategy for the exploitation of high-th
278                            Recent efforts in systems biology studies of infectious diseases have resu
279 analysis of much larger datasets obtained by systems biology studies on a genomic scale.
280 ing the reproducibility and impact of cancer systems biology studies will require widespread method a
281 e common in modern datasets, particularly in systems biology studies.
282                   We conducted a prospective systems biology study of children who differed in their
283 f a large multicenter cohort (BIOSTAT-CHF [A Systems Biology Study to Tailored Treatment in Chronic H
284 ghput microbial genomic sequencing and other systems biology techniques have given novel insight into
285 of limb tendons in adult mice and rats using systems biology techniques.
286 ic dynamical models such as those studied in systems biology there is currently a great need for both
287 c, epigenetic, and endophenotype traits with systems biology to annotate genetic variants, and to fac
288  become one of the most challenging tasks in systems biology to automatically identify protein comple
289    As TGFbeta signalling is complex, we used systems biology to combine experimental and computationa
290  applied to de novo pathway discovery and in systems biology to discover underground metabolism due t
291 bled the fields of metabolic engineering and systems biology to make great strides in interrogating c
292            We have developed a computational systems biology tool, DrugComboExplorer, to identify dri
293                      Using the synthetic and systems biology toolbox, this plug-and-play biosynthetic
294 diators of epithelial dysfunction using both systems biology tools and causality-driven laboratory ex
295 h-dimensional data and computation - defines systems biology, typically accompanied by some notion of
296  need to train students in computational and systems biology using research-grade technologies.
297                                     Taking a systems biology view we show how genetic and epigenetic
298 is an important and widely used algorithm in systems biology, with applications in protein function p
299 nstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes i
300                           Here we describe a systems biology workflow employing plate-based sample pr

 
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