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BMC Systems Biology

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https://www.readbyqxmd.com/read/28724377/combination-therapy-for-melanoma-with-braf-mek-inhibitor-and-immune-checkpoint-inhibitor-a-mathematical-model
#1
Xiulan Lai, Avner Friedman
BACKGROUND: The B-raf gene is mutated in up to 66% of human malignant melanomas, and its protein product, BRAF kinase, is a key part of RAS-RAF-MEK-ERK (MAPK) pathway of cancer cell proliferation. BRAF-targeted therapy induces significant responses in the majority of patients, and the combination BRAF/MEK inhibitor enhances clinical efficacy, but the response to BRAF inhibitor and to BRAF/MEK inhibitor is short lived. On the other hand, treatment of melanoma with an immune checkpoint inhibitor, such as anti-PD-1, has lower response rate but the response is much more durable, lasting for years...
July 19, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28716030/modeling-de-novo-granulation-of-anaerobic-sludge
#2
Anna Doloman, Honey Varghese, Charles D Miller, Nicholas S Flann
BACKGROUND: A unique combination of mechanical, physiochemical and biological forces influences granulation during processes of anaerobic digestion. Understanding this process requires a systems biology approach due to the need to consider not just single-cell metabolic processes, but also the multicellular organization and development of the granule. RESULTS: In this computational experiment, we address the role that physiochemical and biological processes play in granulation and provide a literature-validated working model of anaerobic granule de novo formation...
July 17, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28693620/development-of-an-in-silico-method-for-the-identification-of-subcomplexes-involved-in-the-biogenesis-of-multiprotein-complexes-in-saccharomyces-cerevisiae
#3
Annie Glatigny, Philippe Gambette, Alexa Bourand-Plantefol, Geneviève Dujardin, Marie-Hélène Mucchielli-Giorgi
BACKGROUND: Large sets of protein-protein interaction data coming either from biological experiments or predictive methods are available and can be combined to construct networks from which information about various cell processes can be extracted. We have developed an in silico approach based on these information to model the biogenesis of multiprotein complexes in the yeast Saccharomyces cerevisiae. RESULTS: Firstly, we have built three protein interaction networks by collecting the protein-protein interactions, which involved the subunits of three complexes, from different databases...
July 11, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28693495/an-agent-based-model-of-triple-negative-breast-cancer-the-interplay-between-chemokine-receptor-ccr5-expression-cancer-stem-cells-and-hypoxia
#4
Kerri-Ann Norton, Travis Wallace, Niranjan B Pandey, Aleksander S Popel
BACKGROUND: Triple-negative breast cancer lacks estrogen, progesterone, and HER2 receptors and is thus not possible to treat with targeted therapies for these receptors. Therefore, a greater understanding of triple-negative breast cancer is necessary for the treatment of this cancer type. In previous work from our laboratory, we found that chemokine ligand-receptor CCL5-CCR5 axis is important for the metastasis of human triple-negative breast cancer cell MDA-MB-231 to the lymph nodes and lungs, in a mouse xenograft model...
July 11, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28676050/reconstruction-of-the-microalga-nannochloropsis-salina-genome-scale-metabolic-model-with-applications-to-lipid-production
#5
Nicolás Loira, Sebastian Mendoza, María Paz Cortés, Natalia Rojas, Dante Travisany, Alex Di Genova, Natalia Gajardo, Nicole Ehrenfeld, Alejandro Maass
BACKGROUND: Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. RESULTS: We present iNS934, the first GSMM for N...
July 4, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28659168/gene-expression-profiles-and-signaling-mechanisms-in-%C3%AE-2b-adrenoceptor-evoked-proliferation-of-vascular-smooth-muscle-cells
#6
Anna Huhtinen, Vesa Hongisto, Asta Laiho, Eliisa Löyttyniemi, Dirk Pijnenburg, Mika Scheinin
BACKGROUND: α2-adrenoceptors are important regulators of vascular tone and blood pressure. Regulation of cell proliferation is a less well investigated consequence of α2-adrenoceptor activation. We have previously shown that α2B-adrenoceptor activation stimulates proliferation of vascular smooth muscle cells (VSMCs). This may be important for blood vessel development and plasticity and for the pathology and therapeutics of cardiovascular disorders. The underlying cellular mechanisms have remained mostly unknown...
June 28, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28651594/the-cd4-t-cell-regulatory-network-mediates-inflammatory-responses-during-acute-hyperinsulinemia-a-simulation-study
#7
Mariana E Martinez-Sanchez, Marcia Hiriart, Elena R Alvarez-Buylla
BACKGROUND: Obesity is frequently linked to insulin resistance, high insulin levels, chronic inflammation, and alterations in the behaviour of CD4+ T cells. Despite the biomedical importance of this condition, the system-level mechanisms that alter CD4+ T cell differentiation and plasticity are not well understood. RESULTS: We model how hyperinsulinemia alters the dynamics of the CD4+ T regulatory network, and this, in turn, modulates cell differentiation and plasticity...
June 26, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28646868/comprehensive-benchmarking-of-markov-chain-monte-carlo-methods-for-dynamical-systems
#8
Benjamin Ballnus, Sabine Hug, Kathrin Hatz, Linus Görlitz, Jan Hasenauer, Fabian J Theis
BACKGROUND: In quantitative biology, mathematical models are used to describe and analyze biological processes. The parameters of these models are usually unknown and need to be estimated from experimental data using statistical methods. In particular, Markov chain Monte Carlo (MCMC) methods have become increasingly popular as they allow for a rigorous analysis of parameter and prediction uncertainties without the need for assuming parameter identifiability or removing non-identifiable parameters...
June 24, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28629365/evaluation-and-improvement-of-the-regulatory-inference-for-large-co-expression-networks-with-limited-sample-size
#9
Wenbin Guo, Cristiane P G Calixto, Nikoleta Tzioutziou, Ping Lin, Robbie Waugh, John W S Brown, Runxuan Zhang
BACKGROUND: Co-expression has been widely used to identify novel regulatory relationships using high throughput measurements, such as microarray and RNA-seq data. Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes. For large networks, simulated expression data usually consist of hundreds or thousands of profiles with different perturbations or knock-outs, which is uncommon in real experiments due to their cost and the amount of work required...
June 19, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28619054/hgpec-a-cytoscape-app-for-prediction-of-novel-disease-gene-and-disease-disease-associations-and-evidence-collection-based-on-a-random-walk-on-heterogeneous-network
#10
Duc-Hau Le, Van-Huy Pham
BACKGROUND: Finding gene-disease and disease-disease associations play important roles in the biomedical area and many prioritization methods have been proposed for this goal. Among them, approaches based on a heterogeneous network of genes and diseases are considered state-of-the-art ones, which achieve high prediction performance and can be used for diseases with/without known molecular basis. RESULTS: Here, we developed a Cytoscape app, namely HGPEC, based on a random walk with restart algorithm on a heterogeneous network of genes and diseases...
June 15, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28606124/remodeling-adipose-tissue-through-in-silico-modulation-of-fat-storage-for-the-prevention-of-type-2-diabetes
#11
Thierry Chénard, Frédéric Guénard, Marie-Claude Vohl, André Carpentier, André Tchernof, Rafael J Najmanovich
BACKGROUND: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. RESULTS: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809...
June 12, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28583118/single-cell-study-links-metabolism-with-nutrient-signaling-and-reveals-sources-of-variability
#12
Niek Welkenhuysen, Johannes Borgqvist, Mattias Backman, Loubna Bendrioua, Mattias Goksör, Caroline B Adiels, Marija Cvijovic, Stefan Hohmann
BACKGROUND: The yeast AMPK/SNF1 pathway is best known for its role in glucose de/repression. When glucose becomes limited, the Snf1 kinase is activated and phosphorylates the transcriptional repressor Mig1, which is then exported from the nucleus. The exact mechanism how the Snf1-Mig1 pathway is regulated is not entirely elucidated. RESULTS: Glucose uptake through the low affinity transporter Hxt1 results in nuclear accumulation of Mig1 in response to all glucose concentrations upshift, however with increasing glucose concentration the nuclear localization of Mig1 is more intense...
June 5, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28571567/clostridium-butyricum-maximizes-growth-while-minimizing-enzyme-usage-and-atp-production-metabolic-flux-distribution-of-a-strain-cultured-in-glycerol
#13
Luis Miguel Serrano-Bermúdez, Andrés Fernando González Barrios, Costas D Maranas, Dolly Montoya
BACKGROUND: The increase in glycerol obtained as a byproduct of biodiesel has encouraged the production of new industrial products, such as 1,3-propanediol (PDO), using biotechnological transformation via bacteria like Clostridium butyricum. However, despite the increasing role of Clostridium butyricum as a bio-production platform, its metabolism remains poorly modeled. RESULTS: We reconstructed iCbu641, the first genome-scale metabolic (GSM) model of a PDO producer Clostridium strain, which included 641 genes, 365 enzymes, 891 reactions, and 701 metabolites...
June 1, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28521769/modeling-the-dynamics-of-mouse-iron-body-distribution-hepcidin-is-necessary-but-not-sufficient
#14
Jignesh H Parmar, Grey Davis, Hope Shevchuk, Pedro Mendes
BACKGROUND: Iron is an essential element of most living organisms but is a dangerous substance when poorly liganded in solution. The hormone hepcidin regulates the export of iron from tissues to the plasma contributing to iron homeostasis and also restricting its availability to infectious agents. Disruption of iron regulation in mammals leads to disorders such as anemia and hemochromatosis, and contributes to the etiology of several other diseases such as cancer and neurodegenerative diseases...
May 18, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28511648/a-mathematical-model-of-mechanotransduction-reveals-how-mechanical-memory-regulates-mesenchymal-stem-cell-fate-decisions
#15
Tao Peng, Linan Liu, Adam L MacLean, Chi Wut Wong, Weian Zhao, Qing Nie
BACKGROUND: Mechanical and biophysical properties of the cellular microenvironment regulate cell fate decisions. Mesenchymal stem cell (MSC) fate is influenced by past mechanical dosing (memory), but the mechanisms underlying this process have not yet been well defined. We have yet to understand how memory affects specific cell fate decisions, such as the differentiation of MSCs into neurons, adipocytes, myocytes, and osteoblasts. RESULTS: We study a minimal gene regulatory network permissive of multi-lineage MSC differentiation into four cell fates...
May 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28511646/emergence-of-microbial-diversity-due-to-cross-feeding-interactions-in-a-spatial-model-of-gut-microbial-metabolism
#16
Milan J A van Hoek, Roeland M H Merks
BACKGROUND: The human gut contains approximately 10(14) bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn's disease, and make the microbiota more vulnerable to infestation by harmful species, e...
May 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28476119/parameter-identifiability-analysis-and-visualization-in-large-scale-kinetic-models-of-biosystems
#17
Attila Gábor, Alejandro F Villaverde, Julio R Banga
BACKGROUND: Kinetic models of biochemical systems usually consist of ordinary differential equations that have many unknown parameters. Some of these parameters are often practically unidentifiable, that is, their values cannot be uniquely determined from the available data. Possible causes are lack of influence on the measured outputs, interdependence among parameters, and poor data quality. Uncorrelated parameters can be seen as the key tuning knobs of a predictive model. Therefore, before attempting to perform parameter estimation (model calibration) it is important to characterize the subset(s) of identifiable parameters and their interplay...
May 5, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28472965/parameter-identifiability-based-optimal-observation-remedy-for-biological-networks
#18
Yulin Wang, Hongyu Miao
BACKGROUND: To systematically understand the interactions between numerous biological components, a variety of biological networks on different levels and scales have been constructed and made available in public databases or knowledge repositories. Graphical models such as structural equation models have long been used to describe biological networks for various quantitative analysis tasks, especially key biological parameter estimation. However, limited by resources or technical capacities, partial observation is a common problem in experimental observations of biological networks, and it thus becomes an important problem how to select unobserved nodes for additional measurements such that all unknown model parameters become identifiable...
May 4, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28446174/a-scalable-metabolite-supplementation-strategy-against-antibiotic-resistant-pathogen-chromobacterium-violaceum-induced-by-nad-nadh-imbalance
#19
Deepanwita Banerjee, Dharmeshkumar Parmar, Nivedita Bhattacharya, Avinash D Ghanate, Venkateswarlu Panchagnula, Anu Raghunathan
BACKGROUND: The leading edge of the global problem of antibiotic resistance necessitates novel therapeutic strategies. This study develops a novel systems biology driven approach for killing antibiotic resistant pathogens using benign metabolites. RESULTS: Controlled laboratory evolutions established chloramphenicol and streptomycin resistant pathogens of Chromobacterium. These resistant pathogens showed higher growth rates and required higher lethal doses of antibiotic...
April 26, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28446158/parameter-inference-for-stochastic-single-cell-dynamics-from-lineage-tree-data
#20
Irena Kuzmanovska, Andreas Milias-Argeitis, Jan Mikelson, Christoph Zechner, Mustafa Khammash
BACKGROUND: With the advance of experimental techniques such as time-lapse fluorescence microscopy, the availability of single-cell trajectory data has vastly increased, and so has the demand for computational methods suitable for parameter inference with this type of data. Most of currently available methods treat single-cell trajectories independently, ignoring the mother-daughter relationships and the information provided by the population structure. However, this information is essential if a process of interest happens at cell division, or if it evolves slowly compared to the duration of the cell cycle...
April 26, 2017: BMC Systems Biology
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