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    1723 results match your criteria BMC Systems Biology [Journal]

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    Network pharmacological mechanisms of Vernonia anthelmintica (L.) in the treatment of vitiligo: Isorhamnetin induction of melanogenesis via up-regulation of melanin-biosynthetic genes.
    BMC Syst Biol 2017 Nov 16;11(1):103. Epub 2017 Nov 16.
    Pharmacology department, School of Pharmacy, Shihezi University, Shihezi, 832002, China.
    Background: Vitiligo is a long-term skin disease characterized by the loss of pigment in the skin. The current therapeutic approaches are limited. Although the anti-vitiligo mechanisms of Vernonia anthelmintica (L. Read More

    Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts.
    BMC Syst Biol 2017 Oct 26;11(1):99. Epub 2017 Oct 26.
    Cardiovascular Disease Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
    Background: One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Read More

    Paracrine and autocrine regulation of gene expression by Wnt-inhibitor Dickkopf in wild-type and mutant hepatocytes.
    BMC Syst Biol 2017 Oct 13;11(1):98. Epub 2017 Oct 13.
    Mathematical Modelling of Cellular Processes, Max Delbrueck Center for Molecular Medicine, Robert-Roessle-Str. 10, Berlin, 13125, Germany.
    Background: Cells are able to communicate and coordinate their function within tissues via secreted factors. Aberrant secretion by cancer cells can modulate this intercellular communication, in particular in highly organised tissues such as the liver. Hepatocytes, the major cell type of the liver, secrete Dickkopf (Dkk), which inhibits Wnt/ β-catenin signalling in an autocrine and paracrine manner. Read More

    Informed walks: whispering hints to gene hunters inside networks' jungle.
    BMC Syst Biol 2017 Oct 11;11(1):97. Epub 2017 Oct 11.
    Bioinformatics ERA Chair, The Cyprus Institute of Neurology and Genetics, 6 International Airport Avenue, Ayios Dometios, 2370, Nicosia, Cyprus.
    Background: Systemic approaches offer a different point of view on the analysis of several types of molecular associations as well as on the identification of specific gene communities in several cancer types. However, due to lack of sufficient data needed to construct networks based on experimental evidence, statistical gene co-expression networks are widely used instead. Many efforts have been made to exploit the information hidden in these networks. Read More

    Reconstructing cancer drug response networks using multitask learning.
    BMC Syst Biol 2017 Oct 10;11(1):96. Epub 2017 Oct 10.
    Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
    Background: Translating in vitro results to clinical tests is a major challenge in systems biology. Here we present a new Multi-Task learning framework which integrates thousands of cell line expression experiments to reconstruct drug specific response networks in cancer.

    Results: The reconstructed networks correctly identify several shared key proteins and pathways while simultaneously highlighting many cell type specific proteins. Read More

    A novel interaction perturbation analysis reveals a comprehensive regulatory principle underlying various biochemical oscillators.
    BMC Syst Biol 2017 Oct 10;11(1):95. Epub 2017 Oct 10.
    Laboratory for Systems Biology and Bio-inspired Engineering, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
    Background: Biochemical oscillations play an important role in maintaining physiological and cellular homeostasis in biological systems. The frequency and amplitude of oscillations are regulated to properly adapt to environments by numerous interactions within biomolecular networks. Despite the advances in our understanding of biochemical oscillators, the relationship between the network structure of an oscillator and its regulatory function still remains unclear. Read More

    A systematic analysis of FDA-approved anticancer drugs.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):87. Epub 2017 Oct 3.
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
    Background: The discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment. Repurposing existing drugs that may have unanticipated effects as potential candidates is one way to meet this important goal. Systematic investigation of efficient anticancer drugs could provide valuable insights into trends in the discovery of anticancer drugs, which may contribute to the systematic discovery of new anticancer drugs. Read More

    System modeling reveals the molecular mechanisms of HSC cell cycle alteration mediated by Maff and Egr3 under leukemia.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):91. Epub 2017 Oct 3.
    Shanghai Public Health Clinical Center and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200031, China.
    Background: Molecular mechanisms of the functional alteration of hematopoietic stem cells (HSCs) in leukemic environment attract intensive research interests. As known in previous researches, Maff and Egr3 are two important genes having opposite functions on cell cycle; however, they are both highly expressed in HSCs under leukemia. Hence, exploring the molecular mechanisms of how the genes act on cell cycle will help revealing the functional alteration of HSCs. Read More

    Incorporating genomic, transcriptomic and clinical data: a prognostic and stem cell-like MYC and PRC imbalance in high-risk neuroblastoma.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):92. Epub 2017 Oct 3.
    Section of Hematology and Oncology, Departments of Pediatrics, University of Chicago, Chicago, IL, 60637, USA.
    Background: Previous studies suggested that cancer cells possess traits reminiscent of the biological mechanisms ascribed to normal embryonic stem cells (ESCs) regulated by MYC and Polycomb repressive complex 2 (PRC2). Several poorly differentiated adult tumors showed preferentially high expression levels in targets of MYC, coincident with low expression levels in targets of PRC2. This paper will reveal this ESC-like cancer signature in high-risk neuroblastoma (HR-NB), the most common extracranial solid tumor in children. Read More

    Roles of alternative splicing in modulating transcriptional regulation.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):89. Epub 2017 Oct 3.
    College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
    Background: The ability of a transcription factor to regulate its targets is modulated by a variety of genetic and epigenetic mechanisms. Alternative splicing can modulate gene function by adding or removing certain protein domains, and therefore affect the activity of protein. Reverse engineering of gene regulatory networks using gene expression profiles has proven valuable in dissecting the logical relationships among multiple proteins during the transcriptional regulation. Read More

    Multitype Bellman-Harris branching model provides biological predictors of early stages of adult hippocampal neurogenesis.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):90. Epub 2017 Oct 3.
    Department of Pediatrics, Baylor College of Medicine, Houston, Texas, 77030, USA.
    Background: Adult hippocampal neurogenesis, the process of formation of new neurons, occurs throughout life in the hippocampus. New neurons have been associated with learning and memory as well as mood control, and impaired neurogenesis has been linked to depression, schizophrenia, autism and cognitive decline during aging. Thus, understanding the biological properties of adult neurogenesis has important implications for human health. Read More

    MD-Miner: a network-based approach for personalized drug repositioning.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):86. Epub 2017 Oct 3.
    Department of BioMedical Informatics (BMI), The Ohio State University, Columbus, OH, 43210, USA.
    Background: Due to advances in next generation sequencing technologies and corresponding reductions in cost, it is now attainable to investigate genome-wide gene expression and variants at a patient-level, so as to better understand and anticipate heterogeneous responses to therapy. Consequently, it is feasible to inform personalized drug treatment decisions using personal genomics data. However, these efforts are limited due to a lack of reliable computational approaches for predicting effective drugs for individual patients. Read More

    The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: putting systems biology to work.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):88. Epub 2017 Oct 3.
    The Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, TX, 77030, USA.
    Between December 8-10, 2016, the International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held in Houston, Texas, USA. The conference included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2016, with exciting advances were presented in many areas of systems biology. Read More

    A link prediction approach to cancer drug sensitivity prediction.
    BMC Syst Biol 2017 Oct 3;11(Suppl 5):94. Epub 2017 Oct 3.
    Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, 07102, USA.
    Background: Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. Read More

    Mimvec: a deep learning approach for analyzing the human phenome.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):76. Epub 2017 Sep 21.
    Ministry of Education Key Laboratory of Bioinformatics; Bioinformatics Division, Department of Automation and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, 100084, China.
    Background: The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents. Read More

    Hybrid method to solve HP model on 3D lattice and to probe protein stability upon amino acid mutations.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):93. Epub 2017 Sep 21.
    National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China.
    Background: Predicting protein structure from amino acid sequence is a prominent problem in computational biology. The long range interactions (or non-local interactions) are known as the main source of complexity for protein folding and dynamics and play the dominant role in the compact architecture. Some simple but exact model, such as HP model, captures the pain point for this difficult problem and has important implications to understand the mapping between protein sequence and structure. Read More

    Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):81. Epub 2017 Sep 21.
    School of Mathematics and Computational Science, Xiangtan University, Xiangtan, 411105, China.
    Background: Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. Read More

    A two-step framework for inferring direct protein-protein interaction network from AP-MS data.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):82. Epub 2017 Sep 21.
    School of Software, Dalian University of Technology, Tuqiang Road, Dalian, China.
    Background: Affinity purification-mass spectrometry (AP-MS) has been widely used for generating bait-prey data sets so as to identify underlying protein-protein interactions and protein complexes. However, the AP-MS data sets in terms of bait-prey pairs are highly noisy, where candidate pairs contain many false positives. Recently, numerous computational methods have been developed to identify genuine interactions from AP-MS data sets. Read More

    Modeling and analysis of the Delta-Notch dependent boundary formation in the Drosophila large intestine.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):80. Epub 2017 Sep 21.
    Faculty of Science, Yamaguchi University, Yoshida 1677-1, Yamaguchi, 753-8512, Japan.
    Background: The boundary formation in the Drosophila large intestine is widely studied as an important biological problem. It has been shown that the Delta-Notch signaling pathway plays an essential role in the formation of boundary cells.

    Results: In this paper, we propose a mathematical model for the Delta-Notch dependent boundary formation in the Drosophila large intestine in order to better interpret related experimental findings of this biological phenomenon. Read More

    Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):85. Epub 2017 Sep 21.
    School of Science, Jiangnan University, Wuxi, 214122, China.
    Background: Influenza A virus is prone to mutation and susceptible to human beings and spread in the crowds when affected by the external environment or other factors. It is very necessary to forecast influenza A pandemic outbreak.

    Methods: This paper studies the different states of influenza A in the method of dynamical network biomarkers. Read More

    Understanding biological systems through the lens of data.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):77. Epub 2017 Sep 21.
    Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
    A report of the 10th International Conference on Systems Biology (ISB2016), 19-22 August, Weihai, China. Read More

    Glioma cell fate decisions mediated by Dll1-Jag1-Fringe in Notch1 signaling pathway.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):84. Epub 2017 Sep 21.
    Department of Mathematics, Shanghai University, No.99, Shangda Road, Shanghai, 200444, China.
    Background: The Notch family of proteins plays a vital role in determining cell fates, such as proliferation, differentiation, and apoptosis. It has been shown that Notch1 and its ligands, Dll1 and Jag1, are overexpressed in many glioma cell lines and primary human gliomas. The roles of Notch1 in some cancers have been firmly established, and recent data implicate that it plays important roles in glioma cell fate decisions. Read More

    Improvement of phylogenetic method to analyze compositional heterogeneity.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):79. Epub 2017 Sep 21.
    School of Computer Science and Technology, Tianjin University, 92 Weijin Road, Nankai District, Tianjin, People's Republic of China.
    Background: Phylogenetic analysis is a key way to understand current research in the biological processes and detect theory in evolution of natural selection. The evolutionary relationship between species is generally reflected in the form of phylogenetic trees. Many methods for constructing phylogenetic trees, are based on the optimization criteria. Read More

    NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):75. Epub 2017 Sep 21.
    Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China.
    Background: High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. Read More

    Accelerated parallel algorithm for gene network reverse engineering.
    BMC Syst Biol 2017 Sep 21;11(Suppl 4):83. Epub 2017 Sep 21.
    Department of Systems Biology, 1130 St Nicholas Street, New York, 10032, NY, USA.
    Background: The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE) represents one of the most effective tools to reconstruct gene regulatory networks from large-scale molecular profile datasets. However, previous implementations require intensive computing resources and, in some cases, restrict the number of samples that can be used. These issues can be addressed elegantly in a GPU computing framework, where repeated mathematical computation can be done efficiently, but requires extensive redesign to apply parallel computing techniques to the original serial algorithm, involving detailed optimization efforts based on a deep understanding of both hardware and software architecture. Read More

    An Integrative multi-lineage model of variation in leukopoiesis and acute myelogenous leukemia.
    BMC Syst Biol 2017 Aug 25;11(1):78. Epub 2017 Aug 25.
    Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, 47906, IN, USA.
    Background: Acute myelogenous leukemia (AML) progresses uniquely in each patient. However, patients are typically treated with the same types of chemotherapy, despite biological differences that lead to differential responses to treatment.

    Results: Here we present a multi-lineage multi-compartment model of the hematopoietic system that captures patient-to-patient variation in both the concentration and rates of change of hematopoietic cell populations. Read More

    Cooperative binding mitigates the high-dose hook effect.
    BMC Syst Biol 2017 Aug 14;11(1):74. Epub 2017 Aug 14.
    Department of Neurobiology, Harvard Medical School, Boston, USA.
    Background: The high-dose hook effect (also called prozone effect) refers to the observation that if a multivalent protein acts as a linker between two parts of a protein complex, then increasing the amount of linker protein in the mixture does not always increase the amount of fully formed complex. On the contrary, at a high enough concentration range the amount of fully formed complex actually decreases. It has been observed that allosterically regulated proteins seem less susceptible to this effect. Read More

    Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments.
    BMC Syst Biol 2017 Aug 11;11(1):73. Epub 2017 Aug 11.
    Sanofi, Framingham, MA, USA.
    Background: High-throughput assays are widely used in biological research to select potential targets. One single high-throughput experiment can efficiently study a large number of candidates simultaneously, but is subject to substantial variability. Therefore it is scientifically important to performance quantitative reproducibility analysis to identify reproducible targets with consistent and significant signals across replicate experiments. Read More

    Manatee invariants reveal functional pathways in signaling networks.
    BMC Syst Biol 2017 Jul 28;11(1):72. Epub 2017 Jul 28.
    Molecular Bioinformatics, Institute of Computer Science, Goethe-University Frankfurt am Main, Robert-Mayer-Straße 11-15, Frankfurt am Main, 60325, Germany.
    Background: Signal transduction pathways are important cellular processes to maintain the cell's integrity. Their imbalance can cause severe pathologies. As signal transduction pathways feature complex regulations, they form intertwined networks. Read More

    Snoopy's hybrid simulator: a tool to construct and simulate hybrid biological models.
    BMC Syst Biol 2017 Jul 28;11(1):71. Epub 2017 Jul 28.
    Computer Science Institute, Brandenburg University of Technology, Cottbus, 10 13 44, Germany.
    Background: Hybrid simulation of (computational) biochemical reaction networks, which combines stochastic and deterministic dynamics, is an important direction to tackle future challenges due to complex and multi-scale models. Inherently hybrid computational models of biochemical networks entail two time scales: fast and slow. Therefore, it is intricate to efficiently and accurately analyse them using only either deterministic or stochastic simulation. Read More

    Combination therapy for melanoma with BRAF/MEK inhibitor and immune checkpoint inhibitor: a mathematical model.
    BMC Syst Biol 2017 Jul 19;11(1):70. Epub 2017 Jul 19.
    Mathematical Bioscience Institute & Department of Mathematics, Ohio State University, Columbus, 43210, OH, USA.
    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. Read More

    Modeling de novo granulation of anaerobic sludge.
    BMC Syst Biol 2017 Jul 17;11(1):69. Epub 2017 Jul 17.
    Department of Computer Science, Utah State University, Old Main Hill 420, Logan, 84322-4205, UT, USA.
    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. Read More

    Development of an in silico method for the identification of subcomplexes involved in the biogenesis of multiprotein complexes in Saccharomyces cerevisiae.
    BMC Syst Biol 2017 Jul 11;11(1):67. Epub 2017 Jul 11.
    Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris Sud, Université Paris-Saclay, Avenue de la Terrasse, 91198, Gif-sur-Yvette, France.
    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. Read More

    An agent-based model of triple-negative breast cancer: the interplay between chemokine receptor CCR5 expression, cancer stem cells, and hypoxia.
    BMC Syst Biol 2017 Jul 11;11(1):68. Epub 2017 Jul 11.
    Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA.
    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. Read More

    Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production.
    BMC Syst Biol 2017 Jul 4;11(1):66. Epub 2017 Jul 4.
    Mathomics, Center for Mathematical Modeling, Universidad de Chile, Beauchef 851, 7th Floor, Santiago, Chile.
    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. Read More

    Gene expression profiles and signaling mechanisms in α2B-adrenoceptor-evoked proliferation of vascular smooth muscle cells.
    BMC Syst Biol 2017 Jun 28;11(1):65. Epub 2017 Jun 28.
    Department of Pharmacology, Drug Development and Therapeutics, Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.
    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). Read More

    The CD4+ T cell regulatory network mediates inflammatory responses during acute hyperinsulinemia: a simulation study.
    BMC Syst Biol 2017 Jun 26;11(1):64. Epub 2017 Jun 26.
    Genética Molecular, Desarrollo y Evolución de Plantas, Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, México, Mexico.
    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. Read More

    Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.
    BMC Syst Biol 2017 Jun 24;11(1):63. Epub 2017 Jun 24.
    Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany.
    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. Read More

    Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size.
    BMC Syst Biol 2017 Jun 19;11(1):62. Epub 2017 Jun 19.
    Information and Computational Sciences, The James Hutton Institute, Invergowrie, Dundee, Scotland, DD2 5DA, UK.
    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. Read More

    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.
    BMC Syst Biol 2017 Jun 15;11(1):61. Epub 2017 Jun 15.
    Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
    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. Read More

    Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes.
    BMC Syst Biol 2017 Jun 12;11(1):60. Epub 2017 Jun 12.
    Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada.
    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. Read More

    Single-cell study links metabolism with nutrient signaling and reveals sources of variability.
    BMC Syst Biol 2017 Jun 5;11(1):59. Epub 2017 Jun 5.
    Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96, Gothenburg, Sweden.
    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. Read More

    Clostridium butyricum maximizes growth while minimizing enzyme usage and ATP production: metabolic flux distribution of a strain cultured in glycerol.
    BMC Syst Biol 2017 Jun 1;11(1):58. Epub 2017 Jun 1.
    Bioprocesses and Bioprospecting Group, Universidad Nacional de Colombia. Ciudad Universitaria, Carrera 30 No. 45-03, Bogotá, D.C, Colombia.
    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. Read More

    Modeling the dynamics of mouse iron body distribution: hepcidin is necessary but not sufficient.
    BMC Syst Biol 2017 May 18;11(1):57. Epub 2017 May 18.
    Center for Quantitative Medicine and Department of Cell Biology, UConn Health, Farmington, CT, 06030, USA.
    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. Read More

    A mathematical model of mechanotransduction reveals how mechanical memory regulates mesenchymal stem cell fate decisions.
    BMC Syst Biol 2017 May 16;11(1):55. Epub 2017 May 16.
    Department of Mathematics, Center for Complex Biological Systems, and Center for Mathematical and Computational Biology, University of California, Irvine, CA, 92697, USA.
    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. Read More

    Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism.
    BMC Syst Biol 2017 May 16;11(1):56. Epub 2017 May 16.
    Life Sciences Group, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098 XG, The Netherlands.
    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. Read More

    Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems.
    BMC Syst Biol 2017 May 5;11(1):54. Epub 2017 May 5.
    BioProcess Engineering Group, IIM-CSIC, Eduardo Cabello 6, Vigo, 36208, Spain.
    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. Read More

    Parameter identifiability-based optimal observation remedy for biological networks.
    BMC Syst Biol 2017 May 4;11(1):53. Epub 2017 May 4.
    Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
    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. Read More

    Computational modeling of the cell-autonomous mammalian circadian oscillator.
    BMC Syst Biol 2017 Feb 24;11(Suppl 1):379. Epub 2017 Feb 24.
    ICG SB RAS, Novosibirsk, Russia.
    This review summarizes various mathematical models of cell-autonomous mammalian circadian clock. We present the basics necessary for understanding of the cell-autonomous mammalian circadian oscillator, modern experimental data essential for its reconstruction and some special problems related to the validation of mathematical circadian oscillator models. This work compares existing mathematical models of circadian oscillator and the results of the computational studies of the oscillating systems. Read More

    Theoretical model of mitotic spindle microtubule growth for FRAP curve interpretation.
    BMC Syst Biol 2017 Feb 24;11(Suppl 1):378. Epub 2017 Feb 24.
    Institute of Molecular and Cellular Biology, Novosibirsk, Russia.
    Background: Spindle FRAP curves depend on the kinetic parameters of microtubule polymerization and depolymerization. The empirical FRAP curve proposed earlier permits determination of only one such dynamic parameter, commonly called the "tubulin turnover". The aim of our study was to build a FRAP curve based on an already known kinetic model of microtubule growth. Read More

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