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BMC Systems Biology

Bob Strome, Ian Shenyen Hsu, Mitchell Li Cheong Man, Taraneh Zarin, Alex Nguyen Ba, Alan M Moses
BACKGROUND: The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs). RESULTS: To further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae...
July 3, 2018: BMC Systems Biology
Bin Huang, Dongya Jia, Jingchen Feng, Herbert Levine, José N Onuchic, Mingyang Lu
BACKGROUND: One of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks. RESULTS: We present a user-friendly computational tool for the community to use our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters...
June 19, 2018: BMC Systems Biology
Robert W Smith, Rik P van Rosmalen, Vitor A P Martins Dos Santos, Christian Fleck
BACKGROUND: Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values...
June 19, 2018: BMC Systems Biology
Peter D Karp, Daniel Weaver, Mario Latendresse
BACKGROUND: Reaction gap filling is a computational technique for proposing the addition of reactions to genome-scale metabolic models to permit those models to run correctly. Gap filling completes what are otherwise incomplete models that lack fully connected metabolic networks. The models are incomplete because they are derived from annotated genomes in which not all enzymes have been identified. Here we compare the results of applying an automated likelihood-based gap filler within the Pathway Tools software with the results of manually gap filling the same metabolic model...
June 19, 2018: BMC Systems Biology
Abel Folch-Fortuny, Bas Teusink, Huub C J Hoefsloot, Age K Smilde, Alberto Ferrer
BACKGROUND: A novel framework is proposed to analyse metabolic fluxes in non-steady state conditions, based on the new concept of dynamic elementary mode (dynEM): an elementary mode activated partially depending on the time point of the experiment. RESULTS: Two methods are introduced here: dynamic elementary mode analysis (dynEMA) and dynamic elementary mode regression discriminant analysis (dynEMR-DA). The former is an extension of the recently proposed principal elementary mode analysis (PEMA) method from steady state to non-steady state scenarios...
June 18, 2018: BMC Systems Biology
Rosa D Hernansaiz-Ballesteros, Luca Cardelli, Attila Csikász-Nagy
BACKGROUND: Switch-like and oscillatory dynamical systems are widely observed in biology. We investigate the simplest biological switch that is composed of a single molecule that can be autocatalytically converted between two opposing activity forms. We test how this simple network can keep its switching behaviour under perturbations in the system. RESULTS: We show that this molecule can work as a robust bistable system, even for alterations in the reactions that drive the switching between various conformations...
June 18, 2018: BMC Systems Biology
Colin P McNally, Elhanan Borenstein
BACKGROUND: Metabolic dependencies between microbial species have a significant impact on the assembly and activity of microbial communities. However, the evolutionary origins of such dependencies and the impact of metabolic and genomic architecture on their emergence are not clear. RESULTS: To address these questions, we developed a novel framework, coupling a reductive evolution model with a multi-species genome-scale metabolic model to simulate the evolution of two-species microbial communities...
June 15, 2018: BMC Systems Biology
Stefano Casagranda, Suzanne Touzeau, Delphine Ropers, Jean-Luc Gouzé
BACKGROUND: Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. RESULTS: We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis...
June 14, 2018: BMC Systems Biology
Chunhe Li, Lei Zhang, Qing Nie
BACKGROUND: Spatial pattern formation is a critical issue in developmental biology. Gene expression boundary sharpening has been observed from both experiments and modeling simulations. However, the mechanism to determine the sharpness of the boundary is not fully elucidated. RESULTS: We investigated the boundary sharpening resulted by three biological motifs, interacting with morphogens, and uncovered their probabilistic landscapes. The landscape view, along with calculated average switching time between attractors, provides a natural explanation for the boundary sharpening behavior relying on the noise induced gene state switchings...
June 13, 2018: BMC Systems Biology
Xin Fang, Jonathan M Monk, Nathan Mih, Bin Du, Anand V Sastry, Erol Kavvas, Yara Seif, Larry Smarr, Bernhard O Palsson
BACKGROUND: Escherichia coli is considered a leading bacterial trigger of inflammatory bowel disease (IBD). E. coli isolates from IBD patients primarily belong to phylogroup B2. Previous studies have focused on broad comparative genomic analysis of E. coli B2 isolates, and identified virulence factors that allow B2 strains to reside within human intestinal mucosa. Metabolic capabilities of E. coli strains have been shown to be related to their colonization site, but remain unexplored in IBD-associated strains...
June 11, 2018: BMC Systems Biology
Marcus Thomas, Russell Schwartz
BACKGROUND: The ability of collections of molecules to spontaneously assemble into large functional complexes is central to all cellular processes. Using the viral capsid as a model system for complicated macro-molecular assembly, we develop methods for probing fine details of the process by learning kinetic rate parameters consistent with experimental measures of assembly. We have previously shown that local rule based stochastic simulation methods in conjunction with bulk indirect experimental data can meaningfully constrain the space of possible assembly trajectories and allow inference of experimentally unobservable features of the real system...
June 8, 2018: BMC Systems Biology
Brian C Ross, Mayla Boguslav, Holly Weeks, James C Costello
BACKGROUND: Certain biological processes, such as the development of cancer and immune activation, can be controlled by rare cellular events that are difficult to capture computationally through simulations of individual cells. Information about such rare events can be gleaned from an attractor analysis, for which a variety of methods exist (in particular for Boolean models). However, explicitly simulating a defined mixed population of cells in a way that tracks even the rarest subpopulations remains an open challenge...
June 7, 2018: BMC Systems Biology
Carlos Vazquez-Hernandez, Antonio Loza, Esteban Peguero-Sanchez, Lorenzo Segovia, Rosa-Maria Gutierrez-Rios
BACKGROUND: Metabolic reactions are chemical transformations commonly catalyzed by enzymes. In recent years, the explosion of genomic data and individual experimental characterizations have contributed to the construction of databases and methodologies for the analysis of metabolic networks. Some methodologies based on graph theory organize compound networks into metabolic functional categories without preserving biochemical pathways. Other methods based on chemical group exchange and atom flow trace the conversion of substrates into products in detail, which is useful for inferring metabolic pathways...
May 30, 2018: BMC Systems Biology
Claudia C Preston, Saranya P Wyles, Santiago Reyes, Emily C Storm, Bruce W Eckloff, Randolph S Faustino
BACKGROUND: Atrial fibrillation is a cardiac disease driven by numerous idiopathic etiologies. NUP155 is a nuclear pore complex protein that has been identified as a clinical driver of atrial fibrillation, yet the precise mechanism is unknown. The present study employs a systems biology algorithm to identify effects of NUP155 disruption on cardiogenicity in a model of stem cell-derived differentiation. METHODS: Embryonic stem (ES) cell lines (n = 5) with truncated NUP155 were cultured in parallel with wild type (WT) ES cells (n = 5), and then harvested for RNAseq...
May 30, 2018: BMC Systems Biology
Bruno Pereira, Joana Miguel, Paulo Vilaça, Simão Soares, Isabel Rocha, Sónia Carneiro
BACKGROUND: Actinobacillus succinogenes is a promising bacterial catalyst for the bioproduction of succinic acid from low-cost raw materials. In this work, a genome-scale metabolic model was reconstructed and used to assess the metabolic capabilities of this microorganism under producing conditions. RESULTS: The model, iBP722, was reconstructed based on the functional reannotation of the complete genome sequence of A. succinogenes 130Z and manual inspection of metabolic pathways, covering 1072 enzymatic reactions associated with 722 metabolic genes that involve 713 metabolites...
May 30, 2018: BMC Systems Biology
Bertrand De Meulder, Diane Lefaudeux, Aruna T Bansal, Alexander Mazein, Amphun Chaiboonchoe, Hassan Ahmed, Irina Balaur, Mansoor Saqi, Johann Pellet, Stéphane Ballereau, Nathanaël Lemonnier, Kai Sun, Ioannis Pandis, Xian Yang, Manohara Batuwitage, Kosmas Kretsos, Jonathan van Eyll, Alun Bedding, Timothy Davison, Paul Dodson, Christopher Larminie, Anthony Postle, Julie Corfield, Ratko Djukanovic, Kian Fan Chung, Ian M Adcock, Yi-Ke Guo, Peter J Sterk, Alexander Manta, Anthony Rowe, Frédéric Baribaud, Charles Auffray
BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification...
May 29, 2018: BMC Systems Biology
Steven Woodhouse, Nir Piterman, Christoph M Wintersteiger, Berthold Göttgens, Jasmin Fisher
BACKGROUND: Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge...
May 25, 2018: BMC Systems Biology
Qingyang Zhang
BACKGROUND: Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks...
May 16, 2018: BMC Systems Biology
Frank Kramer, Steffen Just, Tanja Zeller
BACKGROUND: Cardiovascular diseases (CVD) represent one of the most important causes of morbidity and mortality worldwide. Innovative approaches to increase the understanding of the underpinnings of CVD promise to enhance CVD risk assessment and might pave the way to tailored therapies. Within the last years, systems medicine has emerged as a novel tool to study the genetic, molecular and physiological interactions. CONCLUSION: In this review, we provide an overview of the current molecular-experimental, epidemiological and bioinformatical tools applied in systems medicine in the cardiovascular field...
April 25, 2018: BMC Systems Biology
Fei Liu, Siyuan Chen, Monika Heiner, Hengjie Song
BACKGROUND: Uncertainties exist in many biological systems, which can be classified as random uncertainties and fuzzy uncertainties. The former can usually be dealt with using stochastic methods, while the latter have to be handled with such approaches as fuzzy methods. RESULTS: In this paper, we focus on a special type of biological systems that can be described using ordinary differential equations or continuous Petri nets (CPNs), but some kinetic parameters are missing or inaccurate...
April 24, 2018: BMC Systems Biology
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