Search our Database of Scientific Publications and Authors

I’m looking for a

    1698 results match your criteria BMC Systems Biology [Journal]

    1 OF 34

    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

    Understanding key features of bacterial restriction-modification systems through quantitative modeling.
    BMC Syst Biol 2017 Feb 24;11(Suppl 1):377. Epub 2017 Feb 24.
    Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Studentski trg 16, 11000, Belgrade, Serbia.
    Background: Restriction-modification (R-M) systems are rudimentary bacterial immune systems. The main components include restriction enzyme (R), which cuts specific unmethylated DNA sequences, and the methyltransferase (M), which protects the same DNA sequences. The expression of R-M system components is considered to be tightly regulated, to ensure successful establishment in a naïve bacterial host. Read More

    A scalable metabolite supplementation strategy against antibiotic resistant pathogen Chromobacterium violaceum induced by NAD(+)/NADH(+) imbalance.
    BMC Syst Biol 2017 Apr 26;11(1):51. Epub 2017 Apr 26.
    Chemical Engineering Division, CSIR-National Chemical Laboratory, Pune, India.
    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. Read More

    Parameter inference for stochastic single-cell dynamics from lineage tree data.
    BMC Syst Biol 2017 Apr 26;11(1):52. Epub 2017 Apr 26.
    Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, Basel, 4058, Switzerland.
    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. Read More

    SSER: Species specific essential reactions database.
    BMC Syst Biol 2017 Apr 19;11(1):50. Epub 2017 Apr 19.
    Center of Bioinformatics, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
    Background: Essential reactions are vital components of cellular networks. They are the foundations of synthetic biology and are potential candidate targets for antimetabolic drug design. Especially if a single reaction is catalyzed by multiple enzymes, then inhibiting the reaction would be a better option than targeting the enzymes or the corresponding enzyme-encoding gene. Read More

    Membrane potential independent transport of NH3 in the absence of ammonium permeases in Saccharomyces cerevisiae.
    BMC Syst Biol 2017 Apr 17;11(1):49. Epub 2017 Apr 17.
    Department of Biotechnology, Delft University of Technology, van der Maasweg 9, 2629HZ, Delft, The Netherlands.
    Background: Microbial production of nitrogen containing compounds requires a high uptake flux and assimilation of the N-source (commonly ammonium), which is generally coupled with ATP consumption and negatively influences the product yield. In the industrial workhorse Saccharomyces cerevisiae, ammonium (NH4(+)) uptake is facilitated by ammonium permeases (Mep1, Mep2 and Mep3), which transport the NH4(+) ion, resulting in ATP expenditure to maintain the intracellular charge balance and pH by proton export using the plasma membrane-bound H(+)-ATPase.

    Results: To decrease the ATP costs for nitrogen assimilation, the Mep genes were removed, resulting in a strain unable to uptake the NH4(+) ion. Read More

    Mathematical model of TGF-βsignalling: feedback coupling is consistent with signal switching.
    BMC Syst Biol 2017 Apr 13;11(1):48. Epub 2017 Apr 13.
    Department of Surgery (RMH), The University of Melbourne, Parkville, Victoria, 3050, Australia.
    Background: Transforming growth factor β (TGF-β) signalling regulates the development of embryos and tissue homeostasis in adults. In conjunction with other oncogenic changes, long-term perturbation of TGF-β signalling is associated with cancer metastasis. Although TGF-β signalling can be complex, many of the signalling components are well defined, so it is possible to develop mathematical models of TGF-β signalling using reduction and scaling methods. Read More

    An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.
    BMC Syst Biol 2017 Apr 12;11(1):47. Epub 2017 Apr 12.
    Department of Molecular Neuroscience, Institute of Neurology, University College London, Queen Square, London, WC1N, UK.
    Background: Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github. Read More

    SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks.
    BMC Syst Biol 2017 Apr 10;11(1):46. Epub 2017 Apr 10.
    The Babraham Institute, Babraham Campus, Cambridge, CB22 3AT, UK.
    Background: The rapid growth of the number of mathematical models in Systems Biology fostered the development of many tools to simulate and analyse them. The reliability and precision of these tasks often depend on multiple repetitions and they can be optimised if executed as pipelines. In addition, new formal analyses can be performed on these repeat sequences, revealing important insights about the accuracy of model predictions. Read More

    Quantitative evaluation and reversion analysis of the attractor landscapes of an intracellular regulatory network for colorectal cancer.
    BMC Syst Biol 2017 Apr 5;11(1):45. Epub 2017 Apr 5.
    Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
    Background: Cancer reversion, converting the phenotypes of a cancer cell into those of a normal cell, has been sporadically observed throughout history. However, no systematic analysis has been attempted so far.

    Results: To investigate this from a systems biological perspective, we have constructed a logical network model of colorectal tumorigenesis by integrating key regulatory molecules and their interactions from previous experimental data. Read More

    Period doubling cascades of limit cycles in cardiac action potential models as precursors to chaotic early Afterdepolarizations.
    BMC Syst Biol 2017 Apr 4;11(1):42. Epub 2017 Apr 4.
    Institute of Applied Mathematics and Statistics, University of Hohenheim, Schloss 1, Stuttgart, 70599, Germany.
    Background: Early afterdepolarizations (EADs) are pathological voltage oscillations during the repolarization phase of cardiac action potentials (APs). EADs are caused by drugs, oxidative stress or ion channel disease, and they are considered as potential precursors to cardiac arrhythmias in recent attempts to redefine the cardiac drug safety paradigm. The irregular behaviour of EADs observed in experiments has been previously attributed to chaotic EAD dynamics under periodic pacing, made possible by a homoclinic bifurcation in the fast subsystem of the deterministic AP system of differential equations. Read More

    Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare.
    BMC Syst Biol 2017 Apr 4;11(1):44. Epub 2017 Apr 4.
    Center for Bioinformatics, Saarland University, Campus E2.1, Saarbrücken, 66123, Germany.
    Background: Differential analysis of cellular conditions is a key approach towards understanding the consequences and driving causes behind biological processes such as developmental transitions or diseases. The progress of whole-genome expression profiling enabled to conveniently capture the state of a cell's transcriptome and to detect the characteristic features that distinguish cells in specific conditions. In contrast, mapping the physical protein interactome for many samples is experimentally infeasible at the moment. Read More

    Image analysis driven single-cell analytics for systems microbiology.
    BMC Syst Biol 2017 Apr 4;11(1):43. Epub 2017 Apr 4.
    Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilissia, Greece.
    Background: Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. Read More

    Finding low-conductance sets with dense interactions (FLCD) for better protein complex prediction.
    BMC Syst Biol 2017 Mar 14;11(Suppl 3):22. Epub 2017 Mar 14.
    Department of Electrical & Computer Engineering, Texas A and M University, MS 3128, TAMU, College Station, TX, USA.
    Background: Intuitively, proteins in the same protein complexes should highly interact with each other but rarely interact with the other proteins in protein-protein interaction (PPI) networks. Surprisingly, many existing computational algorithms do not directly detect protein complexes based on both of these topological properties. Most of them, depending on mathematical definitions of either "modularity" or "conductance", have their own limitations: Modularity has the inherent resolution problem ignoring small protein complexes; and conductance characterizes the separability of complexes but fails to capture the interaction density within complexes. Read More

    Receptor-guided 3D-QSAR studies, molecular dynamics simulation and free energy calculations of Btk kinase inhibitors.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2). Epub 2017 Mar 14.
    Department of Biomedical Sciences, College of Medicine, Chosun University, 375 Seosuk-dong, Dong-gu, Gwangju, 61452, Republic of Korea.
    Background: Bruton tyrosine kinase (Btk) plays an important role in B-cell development, differentiation, and signaling. It is also found be in involved in male immunodeficiency disease such as X-linked agammaglobulinemia (XLA). Btk is considered as a potential therapeutic target for treating autoimmune diseases and hematological malignancies. Read More

    SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance.
    BMC Syst Biol 2017 Mar 14;11(Suppl 3):20. Epub 2017 Mar 14.
    Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
    Background: Network querying algorithms provide computational means to identify conserved network modules in large-scale biological networks that are similar to known functional modules, such as pathways or molecular complexes. Two main challenges for network querying algorithms are the high computational complexity of detecting potential isomorphism between the query and the target graphs and ensuring the biological significance of the query results.

    Results: In this paper, we propose SEQUOIA, a novel network querying algorithm that effectively addresses these issues by utilizing a context-sensitive random walk (CSRW) model for network comparison and minimizing the network conductance of potential matches in the target network. Read More

    SNP by SNP by environment interaction network of alcoholism.
    BMC Syst Biol 2017 Mar 14;11(Suppl 3):19. Epub 2017 Mar 14.
    Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
    Background: Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. Read More

    A sequence-based method to predict the impact of regulatory variants using random forest.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2). Epub 2017 Mar 14.
    MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China.
    Background: Most disease-associated variants identified by genome-wide association studies (GWAS) exist in noncoding regions. In spite of the common agreement that such variants may disrupt biological functions of their hosting regulatory elements, it remains a great challenge to characterize the risk of a genetic variant within the implicated genome sequence. Therefore, it is essential to develop an effective computational model that is not only capable of predicting the potential risk of a genetic variant but also valid in interpreting how the function of the genome is affected with the occurrence of the variant. Read More

    Prior knowledge guided active modules identification: an integrated multi-objective approach.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2). Epub 2017 Mar 14.
    School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
    Background: Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states.

    Methods: A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Read More

    PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2):15. Epub 2017 Mar 14.
    Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
    Background: Identifying perturbed pathways in a given condition is crucial in understanding biological phenomena. In addition to identifying perturbed pathways individually, pathway analysis should consider interactions among pathways. Currently available pathway interaction prediction methods are based on the existence of overlapping genes between pathways, protein-protein interaction (PPI) or functional similarities. Read More

    Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.
    BMC Syst Biol 2017 Mar 14;11(Suppl 3):21. Epub 2017 Mar 14.
    Department of Computer Science, Virginia Tech, Blacksburg, 24061, VA, USA.
    Background: Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. Read More

    DIGNiFI: Discovering causative genes for orphan diseases using protein-protein interaction networks.
    BMC Syst Biol 2017 Mar 14;11(Suppl 3):23. Epub 2017 Mar 14.
    National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health, Bethesda, 20894, MD, USA.
    Background: An orphan disease is any disease that affects a small percentage of the population. Orphan diseases are a great burden to patients and society, and most of them are genetic in origin. Unfortunately, our current understanding of the genes responsible for inherited orphan diseases is still quite limited. Read More

    Predicting protein-binding regions in RNA using nucleotide profiles and compositions.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2):16. Epub 2017 Mar 14.
    Department of Computer Science and Engineering, Inha University, Incheon, 22212, South Korea.
    Background: Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Read More

    Selecting high-quality negative samples for effectively predicting protein-RNA interactions.
    BMC Syst Biol 2017 Mar 14;11(Suppl 2). Epub 2017 Mar 14.
    School of Computer Science, Fudan University, Handan Road, Shanghai, 200433, China.
    Background: The identification of Protein-RNA Interactions (PRIs) is important to understanding cell activities. Recently, several machine learning-based methods have been developed for identifying PRIs. However, the performance of these methods is unsatisfactory. Read More

    Estimating genome-wide regulatory activity from multi-omics data sets using mathematical optimization.
    BMC Syst Biol 2017 Mar 27;11(1):41. Epub 2017 Mar 27.
    Knowledge Management in Bioinformatics, Computer Science Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany.
    Background: Gene regulation is one of the most important cellular processes, indispensable for the adaptability of organisms and closely interlinked with several classes of pathogenesis and their progression. Elucidation of regulatory mechanisms can be approached by a multitude of experimental methods, yet integration of the resulting heterogeneous, large, and noisy data sets into comprehensive and tissue or disease-specific cellular models requires rigorous computational methods. Recently, several algorithms have been proposed which model genome-wide gene regulation as sets of (linear) equations over the activity and relationships of transcription factors, genes and other factors. Read More

    Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination.
    BMC Syst Biol 2017 Mar 24;11(1):40. Epub 2017 Mar 24.
    Centre for Systems, Dynamics and Control, College of Engineering, Mathematics and Physical Sciences, University of Exeter, North Park Road, Exeter, EX4 4QF, UK.
    Background: Parameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus - pathological ocular oscillations that can be subdivided into different waveform classes. Read More

    1 OF 34