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NPJ Systems Biology and Applications

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https://www.readbyqxmd.com/read/30245847/context-dependent-prediction-of-protein-complexes-by-sicompre
#1
Simone Rizzetto, Petros Moyseos, Bianca Baldacci, Corrado Priami, Attila Csikász-Nagy
Most cellular processes are regulated by groups of proteins interacting together to form protein complexes. Protein compositions vary between different tissues or disease conditions enabling or preventing certain protein-protein interactions and resulting in variations in the complexome. Quantitative and qualitative characterization of context-specific protein complexes will help to better understand context-dependent variations in the physiological behavior of cells. Here, we present SiComPre 1.0, a computational tool that predicts context-specific protein complexes by integrating multi-omics sources...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30210806/the-interaction-of-transcription-factors-controls-the-spatial-layout-of-plant-aerial-stem-cell-niches
#2
Jérémy Gruel, Julia Deichmann, Benoit Landrein, Thomas Hitchcock, Henrik Jönsson
The plant shoot apical meristem holds a stem cell niche from which all aerial organs originate. Using a computational approach we show that a mixture of monomers and heterodimers of the transcription factors WUSCHEL and HAIRY MERISTEM is sufficient to pattern the stem cell niche, and predict that immobile heterodimers form a regulatory "pocket" surrounding the stem cells. The model achieves to reproduce an array of perturbations, including mutants and tissue size modifications. We also show its ability to reproduce the recently observed dynamical shift of the stem cell niche during the development of an axillary meristem...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30181903/dynamic-modeling-of-transcriptional-gene-regulatory-network-uncovers-distinct-pathways-during-the-onset-of-arabidopsis-leaf-senescence
#3
Bharat Mishra, Yali Sun, T C Howton, Nilesh Kumar, M Shahid Mukhtar
Age-dependent senescence is a multifaceted and highly coordinated developmental phase in the life of plants that is manifested with genetic, biochemical and phenotypic continuum. Thus, elucidating the dynamic network modeling and simulation of molecular events, in particular gene regulatory network during the onset of senescence is essential. Here, we constructed a computational pipeline that integrates senescence-related co-expression networks with transcription factor (TF)-promoter relationships and microRNA (miR)-target interactions...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30181902/prevalence-and-patterns-of-higher-order-drug-interactions-in-escherichia-coli
#4
Elif Tekin, Cynthia White, Tina Manzhu Kang, Nina Singh, Mauricio Cruz-Loya, Robert Damoiseaux, Van M Savage, Pamela J Yeh
Interactions and emergent processes are essential for research on complex systems involving many components. Most studies focus solely on pairwise interactions and ignore higher-order interactions among three or more components. To gain deeper insights into higher-order interactions and complex environments, we study antibiotic combinations applied to pathogenic Escherichia coli and obtain unprecedented amounts of detailed data (251 two-drug combinations, 1512 three-drug combinations, 5670 four-drug combinations, and 13608 five-drug combinations)...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30181901/redefining-environmental-exposure-for-disease-etiology
#5
Stephen M Rappaport
Etiological studies of human exposures to environmental factors typically rely on low-throughput methods that target only a few hundred chemicals or mixtures. In this Perspectives article, I outline how environmental exposure can be defined by the blood exposome-the totality of chemicals circulating in blood. The blood exposome consists of chemicals derived from both endogenous and exogenous sources. Endogenous chemicals are represented by the human proteome and metabolome, which establish homeostatic networks of functional molecules...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30155271/a-landscape-view-on-the-interplay-between-emt-and-cancer-metastasis
#6
Chunhe Li, Gabor Balazsi
The epithelial-mesenchymal transition (EMT) is a basic developmental process that converts epithelial cells to mesenchymal cells. Although EMT might promote cancer metastasis, the molecular mechanisms for it remain to be fully clarified. To address this issue, we constructed an EMT-metastasis gene regulatory network model and quantified the potential landscape of cancer metastasis-promoting system computationally. We identified four steady-state attractors on the landscape, which separately characterize anti-metastatic (A), metastatic (M), and two other intermediate (I1 and I2) cell states...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30131870/multi-scale-whole-system-models-of-liver-metabolic-adaptation-to-fat-and-sugar-in-non-alcoholic-fatty-liver-disease
#7
Elaina M Maldonado, Ciarán P Fisher, Dawn J Mazzatti, Amy L Barber, Marcus J Tindall, Nicholas J Plant, Andrzej M Kierzek, J Bernadette Moore
Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue associated with high fat, high sugar diets. However, the molecular mechanisms mediating NAFLD pathogenesis are only partially understood. Here we adopt an iterative multi-scale, systems biology approach coupled to in vitro experimentation to investigate the roles of sugar and fat metabolism in NAFLD pathogenesis. The use of fructose as a sweetening agent is controversial; to explore this, we developed a predictive model of human monosaccharide transport, signalling and metabolism...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30131869/flux-dependent-graphs-for-metabolic-networks
#8
Mariano Beguerisse-Díaz, Gabriel Bosque, Diego Oyarzún, Jesús Picó, Mauricio Barahona
Cells adapt their metabolic fluxes in response to changes in the environment. We present a framework for the systematic construction of flux-based graphs derived from organism-wide metabolic networks. Our graphs encode the directionality of metabolic flows via edges that represent the flow of metabolites from source to target reactions. The methodology can be applied in the absence of a specific biological context by modelling fluxes probabilistically, or can be tailored to different environmental conditions by incorporating flux distributions computed through constraint-based approaches such as Flux Balance Analysis...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30083390/modeling-gene-regulatory-networks-to-describe-cell-fate-transitions-and-predict-master-regulators
#9
Pierre-Etienne Cholley, Julien Moehlin, Alexia Rohmer, Vincent Zilliox, Samuel Nicaise, Hinrich Gronemeyer, Marco Antonio Mendoza-Parra
Complex organisms originate from and are maintained by the information encoded in the genome. A major challenge of systems biology is to develop algorithms that describe the dynamic regulation of genome functions from large omics datasets. Here, we describe TETRAMER, which reconstructs gene-regulatory networks from temporal transcriptome data during cell fate transitions to predict "master" regulators by simulating cascades of temporal transcription-regulatory events.
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30083389/using-quantitative-systems-pharmacology-to-evaluate-the-drug-efficacy-of-cox-2-and-5-lox-inhibitors-in-therapeutic-situations
#10
Christoph Thiel, Ines Smit, Vanessa Baier, Henrik Cordes, Brigida Fabry, Lars Mathias Blank, Lars Kuepfer
A quantitative analysis of dose-response relationships is essential in preclinical and clinical drug development in order to optimize drug efficacy and safety, respectively. However, there is a lack of quantitative understanding about the dynamics of pharmacological drug-target interactions in biological systems. In this study, a quantitative systems pharmacology (QSP) approach is applied to quantify the drug efficacy of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors by coupling physiologically based pharmacokinetic models, at the whole-body level, with affected biological networks, at the cellular scale...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/30083388/from-metagenomic-data-to-personalized-in-silico-microbiotas-predicting-dietary-supplements-for-crohn-s-disease
#11
Eugen Bauer, Ines Thiele
Crohn's disease (CD) is associated with an ecological imbalance of the intestinal microbiota, consisting of hundreds of species. The underlying complexity as well as individual differences between patients contributes to the difficulty to define a standardized treatment. Computational modeling can systematically investigate metabolic interactions between gut microbes to unravel mechanistic insights. In this study, we integrated metagenomic data of CD patients and healthy controls with genome-scale metabolic models into personalized in silico microbiotas...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29977602/systems-pharmacology-using-mass-spectrometry-identifies-critical-response-nodes-in-prostate-cancer
#12
H Alexander Ebhardt, Alex Root, Yansheng Liu, Nicholas Paul Gauthier, Chris Sander, Ruedi Aebersold
In the United States alone one in five newly diagnosed cancers in men are prostate carcinomas (PCa). Androgen receptor (AR) status and the PI3K-AKT-mTOR signal transduction pathway are critical in PCa. After initial response to single drugs targeting these pathways resistance often emerges, indicating the need for combination therapy. Here, we address the question of efficacy of drug combinations and development of resistance mechanisms to targeted therapy by a systems pharmacology approach. We combine targeted perturbation with detailed observation of the molecular response by mass spectrometry...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29977601/controllability-in-an-islet-specific-regulatory-network-identifies-the-transcriptional-factor-nfatc4-which-regulates-type-2-diabetes-associated-genes
#13
Amitabh Sharma, Arda Halu, Julius L Decano, Megha Padi, Yang-Yu Liu, Rashmi B Prasad, Joao Fadista, Marc Santolini, Jörg Menche, Scott T Weiss, Marc Vidal, Edwin K Silverman, Masanori Aikawa, Albert-László Barabási, Leif Groop, Joseph Loscalzo
Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p -values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29977600/a-network-of-epigenomic-and-transcriptional-cooperation-encompassing-an-epigenomic-master-regulator-in-cancer
#14
Stephen Wilson, Fabian Volker Filipp
Coordinated experiments focused on transcriptional responses and chromatin states are well-equipped to capture different epigenomic and transcriptomic levels governing the circuitry of a regulatory network. We propose a workflow for the genome-wide identification of epigenomic and transcriptional cooperation to elucidate transcriptional networks in cancer. Gene promoter annotation in combination with network analysis and sequence-resolution of enriched transcriptional motifs in epigenomic data reveals transcription factor families that act synergistically with epigenomic master regulators...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29900006/model-based-identification-of-tnf%C3%AE-induced-ikk%C3%AE-mediated-and-i%C3%AE%C2%BAb%C3%AE-mediated-regulation-of-nf%C3%AE%C2%BAb-signal-transduction-as-a-tool-to-quantify-the-impact-of-drug-induced-liver-injury-compounds
#15
Angela Oppelt, Daniel Kaschek, Suzanna Huppelschoten, Rowena Sison-Young, Fang Zhang, Marie Buck-Wiese, Franziska Herrmann, Sebastian Malkusch, Carmen L Krüger, Mara Meub, Benjamin Merkt, Lea Zimmermann, Amy Schofield, Robert P Jones, Hassan Malik, Marcel Schilling, Mike Heilemann, Bob van de Water, Christopher E Goldring, B Kevin Park, Jens Timmer, Ursula Klingmüller
Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29900005/mapping-biological-process-relationships-and-disease-perturbations-within-a-pathway-network
#16
Ruth Stoney, David L Robertson, Goran Nenadic, Jean-Marc Schwartz
Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29872544/systems-medicine-disease-maps-community-driven-comprehensive-representation-of-disease-mechanisms
#17
Alexander Mazein, Marek Ostaszewski, Inna Kuperstein, Steven Watterson, Nicolas Le Novère, Diane Lefaudeux, Bertrand De Meulder, Johann Pellet, Irina Balaur, Mansoor Saqi, Maria Manuela Nogueira, Feng He, Andrew Parton, Nathanaël Lemonnier, Piotr Gawron, Stephan Gebel, Pierre Hainaut, Markus Ollert, Ugur Dogrusoz, Emmanuel Barillot, Andrei Zinovyev, Reinhard Schneider, Rudi Balling, Charles Auffray
The development of computational approaches in systems biology has reached a state of maturity that allows their transition to systems medicine. Despite this progress, intuitive visualisation and context-dependent knowledge representation still present a major bottleneck. In this paper, we describe the Disease Maps Project, an effort towards a community-driven computationally readable comprehensive representation of disease mechanisms. We outline the key principles and the framework required for the success of this initiative, including use of best practices, standards and protocols...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29872543/a-data-driven-knowledge-based-approach-to-biomarker-discovery-application-to-circulating-microrna-markers-of-colorectal-cancer-prognosis
#18
Fatemeh Vafaee, Connie Diakos, Michaela B Kirschner, Glen Reid, Michael Z Michael, Lisa G Horvath, Hamid Alinejad-Rokny, Zhangkai Jason Cheng, Zdenka Kuncic, Stephen Clarke
Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29872542/a-machine-learning-approach-to-predict-metabolic-pathway-dynamics-from-time-series-multiomics-data
#19
Zak Costello, Hector Garcia Martin
New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict biological behavior after modifying the corresponding genotype. Kinetic models have traditionally been used to predict pathway dynamics in bioengineered systems, but they take significant time to develop, and rely heavily on domain expertise. Here, we show that the combination of machine learning and abundant multiomics data (proteomics and metabolomics) can be used to effectively predict pathway dynamics in an automated fashion...
2018: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/29872541/pathway-crosstalk-enables-cells-to-interpret-tgf-%C3%AE-duration
#20
Jingyu Zhang, Xiao-Jun Tian, Yi-Jiun Chen, Weikang Wang, Simon Watkins, Jianhua Xing
The detection and transmission of the temporal quality of intracellular and extracellular signals is an essential cellular mechanism. It remains largely unexplored how cells interpret the duration information of a stimulus. In this paper, we performed an integrated quantitative and computational analysis on TGF-β induced activation of SNAIL1, a key transcription factor that regulates several subsequent cell fate decisions such as apoptosis and epithelial-to-mesenchymal transition. We demonstrate that crosstalk among multiple TGF-β activated pathways forms a relay from SMAD to GLI1 that initializes and maintains SNAILl expression, respectively...
2018: NPJ Systems Biology and Applications
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