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    1838 results match your criteria BMC Systems Biology [Journal]

    1 OF 37

    Metabolic model-based analysis of the emergence of bacterial cross-feeding via extensive gene loss.
    BMC Syst Biol 2018 Jun 15;12(1):69. Epub 2018 Jun 15.
    Department of Genome Sciences, University of Washington, Seattle, WA, USA.
    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. Read More

    Landscape reveals critical network structures for sharpening gene expression boundaries.
    BMC Syst Biol 2018 Jun 13;12(1):67. Epub 2018 Jun 13.
    Department of Mathematics, University of California, Irvine, 92697, USA.
    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. Read More

    Principal process analysis of biological models.
    BMC Syst Biol 2018 Jun 14;12(1):68. Epub 2018 Jun 14.
    Université Côte d'Azur, Inria, INRA, CNRS, UPMC Univ Paris 06, Biocore team, Sophia Antipolis, France.
    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. Read More

    Escherichia coli B2 strains prevalent in inflammatory bowel disease patients have distinct metabolic capabilities that enable colonization of intestinal mucosa.
    BMC Syst Biol 2018 Jun 11;12(1):66. Epub 2018 Jun 11.
    Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, 92093, CA, USA.
    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. Read More

    A method for efficient Bayesian optimization of self-assembly systems from scattering data.
    BMC Syst Biol 2018 Jun 8;12(1):65. Epub 2018 Jun 8.
    Computational Biology Department, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, USA.
    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. Read More

    Simulating heterogeneous populations using Boolean models.
    BMC Syst Biol 2018 Jun 7;12(1):64. Epub 2018 Jun 7.
    Computational Bioscience Program, University of Colorado Anschutz Medical Campus, 12801 E. 17th Ave., Aurora, CO, 80045, USA.
    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. Read More

    Identification of reaction organization patterns that naturally cluster enzymatic transformations.
    BMC Syst Biol 2018 May 30;12(1):63. Epub 2018 May 30.
    Departamento de Microbiología Molecular, Instituto de Biotecnología Universidad Nacional Autónoma de México, Apdo, Postal 510-3, 62250, Cuernavaca, Morelos, Mexico.
    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. Read More

    NUP155 insufficiency recalibrates a pluripotent transcriptome with network remodeling of a cardiogenic signaling module.
    BMC Syst Biol 2018 May 30;12(1):62. Epub 2018 May 30.
    Genetics and Genomics Group, Sanford Research, 2301 E. 60th Street N, Sioux Falls, SD, 57104, USA.
    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. Read More

    A computational framework for complex disease stratification from multiple large-scale datasets.
    BMC Syst Biol 2018 May 29;12(1):60. Epub 2018 May 29.
    European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, EISBM, 50 Avenue Tony Garnier, 69007, Lyon, France.
    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. Read More

    Reconstruction of a genome-scale metabolic model for Actinobacillus succinogenes 130Z.
    BMC Syst Biol 2018 May 30;12(1):61. Epub 2018 May 30.
    SilicoLife Lda, Rua do Canastreiro 15, 4715-387, Braga, Portugal.
    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. Read More

    SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.
    BMC Syst Biol 2018 May 25;12(1):59. Epub 2018 May 25.
    Microsoft Research Cambridge, 21 Station Road, Cambridge, CB1 2FB, UK.
    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. Read More

    A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.
    BMC Syst Biol 2018 May 16;12(1):58. Epub 2018 May 16.
    Department of Mathematical Sciences, University of Arkansas, Fayetteville, AR 72701, USA.
    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. Read More

    Modeling biological systems with uncertain kinetic data using fuzzy continuous Petri nets.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):42. Epub 2018 Apr 24.
    School of Software Engineering, South China University of Technology, Guangzhou, 510006, People's Republic of China.
    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. Read More

    Detecting complexes from edge-weighted PPI networks via genes expression analysis.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):40. Epub 2018 Apr 24.
    School of Computer Science and Technology, Tianjin University, Tianjin, People's Republic of China.
    Background: Identifying complexes from PPI networks has become a key problem to elucidate protein functions and identify signal and biological processes in a cell. Proteins binding as complexes are important roles of life activity. Accurate determination of complexes in PPI networks is crucial for understanding principles of cellular organization. Read More

    KF-finder: identification of key factors from host-microbial networks in cervical cancer.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):54. Epub 2018 Apr 24.
    School of Computer Science, Northwestern Polytechnical University, West Youyi Road 127, Xi'an, 710072, China.
    Background: The human body is colonized by a vast number of microbes. Microbiota can benefit many normal life processes, but can also cause many diseases by interfering the regular metabolism and immune system. Recent studies have demonstrated that the microbial community is closely associated with various types of cell carcinoma. Read More

    Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):39. Epub 2018 Apr 24.
    Department of Bioinformatics and Biostatistics, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
    Background: Diamond-Blackfan anemia (DBA) is a congenital erythroid aplasia that usually presents in infancy. In order to explore the molecular mechanisms of wild and mutated samples from DBA patients were exposed to bioinformatics investigation. Biological network of differentially expressed genes was constructed. Read More

    70ProPred: a predictor for discovering sigma70 promoters based on combining multiple features.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):44. Epub 2018 Apr 24.
    School of Computer Science and Technology, Tianjin University, Tianjin, 300072, China.
    Background: Promoter is an important sequence regulation element, which is in charge of gene transcription initiation. In prokaryotes, σ promoters regulate the transcription of most genes. The promoter recognition has been a crucial part of gene structure recognition. Read More

    Transcriptomic and metabolic flux analyses reveal shift of metabolic patterns during rice grain development.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):47. Epub 2018 Apr 24.
    Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200032, People's Republic of China.
    Background: Rice (Oryza sativa) is one of the most important grain crops, which serves as food source for nearly half of the world population. The study of rice development process as well as related strategies for production has made significant progress. However, the comprehensive study on development of different rice tissues at both transcriptomic and metabolic flux level across different stages was lacked. Read More

    Feedback regulation in a stem cell model with acute myeloid leukaemia.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):43. Epub 2018 Apr 24.
    Department of Mathematics, Shanghai University, Shangda Road No.99, Shanghai, 200444, China.
    Background: The haematopoietic lineages with leukaemia lineages are considered in this paper. In particular, we mainly consider that haematopoietic lineages are tightly controlled by negative feedback inhibition of end-product. Actually, leukemia has been found 100 years ago. Read More

    PPI network analyses of human WD40 protein family systematically reveal their tendency to assemble complexes and facilitate the complex predictions.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):41. Epub 2018 Apr 24.
    Lab of Computational Chemistry and Drug Design, Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen, 518055, People's Republic of China.
    Background: WD40 repeat proteins constitute one of the largest families in eukaryotes, and widely participate in various fundamental cellular processes by interacting with other molecules. Based on individual WD40 proteins, previous work has demonstrated that their structural characteristics should confer great potential of interaction and complex formation, and has speculated that they may serve as hubs in the protein-protein interaction (PPI) network. However, what roles the whole family plays in organizing the PPI network, and whether this information can be utilized in complex prediction remain unclear. Read More

    Functional enrichment analysis based on long noncoding RNA associations.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):45. Epub 2018 Apr 24.
    Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan.
    Background: Differential gene expression analysis using RNA-seq data is a popular approach for discovering specific regulation mechanisms under certain environmental settings. Both gene ontology (GO) and KEGG pathway enrichment analysis are major processes for investigating gene groups that participate in common biological responses or possess related functions. However, traditional approaches based on differentially expressed genes only detect a few significant GO terms and pathways, which are frequently insufficient to explain all-inclusive gene regulation mechanisms. Read More

    Fixation probability of a beneficial mutation conferring decreased generation time in changing environments.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):48. Epub 2018 Apr 24.
    Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
    Background: One central building block of population genetics is the fixation probability. It is a probabilistic understanding of the eventual fate of new mutations. Moreover, the fixation probability of new beneficial mutations plays an important effect on the adaptation of populations to environmental challenges. Read More

    Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):56. Epub 2018 Apr 24.
    Mathematical Intelligence Application Lab, Institute for Mathematical Sciences, Renmin University of China, Beijing, China.
    Background: Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abdomen, makes detailed texture information of objects important in segmentation algorithm. According to our observations, however, the structures of previous networks, such as the Richer Feature Convolutional Network (RCF), are too coarse to segment the object (pancreas) accurately, especially the edge. Read More

    Multi-target drug repositioning by bipartite block-wise sparse multi-task learning.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):55. Epub 2018 Apr 24.
    Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
    Background: Finding potential drug targets is a crucial step in drug discovery and development. Recently, resources such as the Library of Integrated Network-Based Cellular Signatures (LINCS) L1000 database provide gene expression profiles induced by various chemical and genetic perturbations and thereby make it possible to analyze the relationship between compounds and gene targets at a genome-wide scale. Current approaches for comparing the expression profiles are based on pairwise connectivity mapping analysis. Read More

    Improved flower pollination algorithm for identifying essential proteins.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):46. Epub 2018 Apr 24.
    Key Laboratory of Systems Biology, CAS center for Excellence in Molecular Cell Science, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
    Background: Essential proteins are necessary for the survival and development of cells. The identification of essential proteins can help to understand the minimal requirements for cellular life and it also plays an important role in the disease genes study and drug design. With the development of high-throughput techniques, a large amount of protein-protein interactions data is available to predict essential proteins at the network level. Read More

    Differential networking meta-analysis of gastric cancer across Asian and American racial groups.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):51. Epub 2018 Apr 24.
    Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai, 201203, People's Republic of China.
    Background: Gastric Carcinoma is one of the most lethal cancer around the world, and is also the most common cancers in Eastern Asia. A lot of differentially expressed genes have been detected as being associated with Gastric Carcinoma (GC) progression, however, little is known about the underlying dysfunctional regulation mechanisms. To address this problem, we previously developed a differential networking approach that is characterized by involving differential coexpression analysis (DCEA), stage-specific gene regulatory network (GRN) modelling and differential regulation networking (DRN) analysis. Read More

    Integrating data- and model-driven strategies in systems biology.
    BMC Syst Biol 2018 Apr 24;12(Suppl 4):38. Epub 2018 Apr 24.
    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 11th International Conference on Systems Biology (ISB2017), 18-21 August, Shenzhen, China. Read More

    New perspectives: systems medicine in cardiovascular disease.
    BMC Syst Biol 2018 Apr 25;12(1):57. Epub 2018 Apr 25.
    Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Martinistrasse 52, 20246, Hamburg, Germany.
    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. Read More

    ncRNA-disease association prediction based on sequence information and tripartite network.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1):37. Epub 2018 Apr 11.
    Department of Information Science, Toho University, Miyama 2-2-1, Funabashi, Chiba, 274-8510, Japan.
    Background: Current technology has demonstrated that mutation and deregulation of non-coding RNAs (ncRNAs) are associated with diverse human diseases and important biological processes. Therefore, developing a novel computational method for predicting potential ncRNA-disease associations could benefit pathologists in understanding the correlation between ncRNAs and disease diagnosis, treatment, and prevention. However, only a few studies have investigated these associations in pathogenesis. Read More

    Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1):11. Epub 2018 Apr 11.
    School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
    Background: 25% of breast cancer patients suffer from aggressive HER2-positive tumours that are characterised by overexpression of the HER2 protein or by its increased tyrosine kinase activity. Herceptin is a major drug used to treat HER2 positive breast cancer. Understanding the molecular events that occur when breast cancer cells are exposed to Herceptin is therefore of significant importance. Read More

    KDiamend: a package for detecting key drivers in a molecular ecological network of disease.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1). Epub 2018 Apr 11.
    Department of Computer Science, City University of Hong Kong, Tat Chee Avenue, Hong Kong, China.
    Background: Microbial abundance profiles are applied widely to understand diseases from the aspect of microbial communities. By investigating the abundance associations of species or genes, we can construct molecular ecological networks (MENs). The MENs are often constructed by calculating the Pearson correlation coefficient (PCC) between genes. Read More

    Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1). Epub 2018 Apr 11.
    Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
    Background: Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/inhibition) of protein-protein interactions (PPIs). Read More

    Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1). Epub 2018 Apr 11.
    Center for Computational Systems Biology, Shanghai Key Laboratory for Contemporary Applied Mathematics, School of Mathematical Sciences, Fudan University, No.220 Handan Road, Shanghai, 200433, China.
    Background: Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules.

    Methods: We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. Read More

    Composite mathematical modeling of calcium signaling behind neuronal cell death in Alzheimer's disease.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1):10. Epub 2018 Apr 11.
    Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
    Background: Alzheimer's disease (AD) is a progressive neurological disorder, recognized as the most common cause of dementia affecting people aged 65 and above. AD is characterized by an increase in amyloid metabolism, and by the misfolding and deposition of β-amyloid oligomers in and around neurons in the brain. These processes remodel the calcium signaling mechanism in neurons, leading to cell death via apoptosis. Read More

    Discovery of Boolean metabolic networks: integer linear programming based approach.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1). Epub 2018 Apr 11.
    School of Mathematics and Statistics, Xi'An Jiaotong University, No.28 West Xianning Road, Xi'An, 710049, China.
    Background: Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Read More

    Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1):14. Epub 2018 Apr 11.
    Department of Computer Science, The University of Hong Kong, Hong Kong, China.
    Background: Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Read More

    Counting motifs in dynamic networks.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1). Epub 2018 Apr 11.
    Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA.
    Background: A network motif is a sub-network that occurs frequently in a given network. Detection of such motifs is important since they uncover functions and local properties of the given biological network. Finding motifs is however a computationally challenging task as it requires solving the costly subgraph isomorphism problem. Read More

    Estimation of diffusion constants from single molecular measurement without explicit tracking.
    BMC Syst Biol 2018 Apr 11;12(Suppl 1):15. Epub 2018 Apr 11.
    Quantitative Immunology Research Unit, Immunology Frontier Research Center, Osaka University, 3-1 Yamada-oka, Suita, Osaka, 565-0871, Japan.
    Background: Time course measurement of single molecules on a cell surface provides detailed information about the dynamics of the molecules that would otherwise be inaccessible. To extract the quantitative information, single particle tracking (SPT) is typically performed. However, trajectories extracted by SPT inevitably have linking errors when the diffusion speed of single molecules is high compared to the scale of the particle density. Read More

    Evolution of computational models in BioModels Database and the Physiome Model Repository.
    BMC Syst Biol 2018 Apr 12;12(1):53. Epub 2018 Apr 12.
    Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany.
    Background: A useful model is one that is being (re)used. The development of a successful model does not finish with its publication. During reuse, models are being modified, i. Read More

    Putative human sperm Interactome: a networks study.
    BMC Syst Biol 2018 Apr 11;12(1):52. Epub 2018 Apr 11.
    Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy.
    Background: For over sixty years, it has been known that mammalian spermatozoa immediately after ejaculation are virtually infertile. They became able to fertilize only after they reside for long time (hours to days) within female genital tract where they complete their functional maturation, the capacitation. This process is finely regulated by the interaction with the female environment and involves, in spermatozoa, a myriad of molecules as messengers and target of signals. Read More

    The innate immune response to ischemic injury: a multiscale modeling perspective.
    BMC Syst Biol 2018 Apr 10;12(1):50. Epub 2018 Apr 10.
    Center for Vascular Biology, Department of Cell Biology, University of Connecticut School of Medicine, Farmington, 06030, CT, USA.
    Background: Cell death as a result of ischemic injury triggers powerful mechanisms regulated by germline-encoded Pattern Recognition Receptors (PRRs) with shared specificity that recognize invading pathogens and endogenous ligands released from dying cells, and as such are essential to human health. Alternatively, dysregulation of these mechanisms contributes to extreme inflammation, deleterious tissue damage and impaired healing in various diseases. The Toll-like receptors (TLRs) are a prototypical family of PRRs that may be powerful anti-inflammatory targets if agents can be designed that antagonize their harmful effects while preserving host defense functions. Read More

    The phenotype control kernel of a biomolecular regulatory network.
    BMC Syst Biol 2018 Apr 5;12(1):49. Epub 2018 Apr 5.
    Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
    Background: Controlling complex molecular regulatory networks is getting a growing attention as it can provide a systematic way of driving any cellular state to a desired cell phenotypic state. A number of recent studies suggested various control methods, but there is still deficiency in finding out practically useful control targets that ensure convergence of any initial network state to one of attractor states corresponding to a desired cell phenotype.

    Results: To find out practically useful control targets, we introduce a new concept of phenotype control kernel (PCK) for a Boolean network, defined as the collection of all minimal sets of control nodes having their fixed state values that can generate all possible control sets which eventually drive any initial state to one of attractor states corresponding to a particular cell phenotype of interest. Read More

    Identification of new progestogen-associated networks in mammalian ovulation using bioinformatics.
    BMC Syst Biol 2018 Apr 3;12(1):36. Epub 2018 Apr 3.
    College of Bioengineering, Chongqing University, Chongqing, 400030, China.
    Background: Progesterone plays an essential role in mammalian ovulation. Although much is known about this process, the gene networks involved in ovulation have yet to be established. When analyze the mechanisms of ovulation, we often need to determine key genes or pathways to investigate the reproduction features. Read More

    Systems biology analysis of mitogen activated protein kinase inhibitor resistance in malignant melanoma.
    BMC Syst Biol 2018 Apr 4;12(1):33. Epub 2018 Apr 4.
    Systems Biology and Cancer Metabolism, Program for Quantitative Systems Biology, University of California Merced, 2500 North Lake Road, Merced, CA, 95343, USA.
    Background: Kinase inhibition in the mitogen activated protein kinase (MAPK) pathway is a standard therapy for cancer patients with activating BRAF mutations. However, the anti-tumorigenic effect and clinical benefit are only transient, and tumors are prone to treatment resistance and relapse. To elucidate mechanistic insights into drug resistance, we have established an in vitro cellular model of MAPK inhibitor resistance in malignant melanoma. Read More

    Mathematical modelling of interacting mechanisms for hypoxia mediated cell cycle commitment for mesenchymal stromal cells.
    BMC Syst Biol 2018 Apr 2;12(1):35. Epub 2018 Apr 2.
    Department of Engineering Science, University of Oxford, Oxford, UK.
    Background: Existing experimental data have shown hypoxia to be an important factor affecting the proliferation of mesenchymal stromal cells (MSCs), but the contrasting observations made at various hypoxic levels raise the questions of whether hypoxia accelerates proliferation, and how. On the other hand, in order to meet the increasing demand of MSCs, an optimised bioreactor control strategy is needed to enhance in vitro production.

    Results: A comprehensive, single-cell mathematical model has been constructed in this work, which combines cellular oxygen sensing with hypoxia-mediated cell cycle progression to predict cell cycle commitment as a proxy to proliferation rate. Read More

    Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.
    BMC Syst Biol 2018 Mar 21;12(Suppl 3):32. Epub 2018 Mar 21.
    LS2N, UMR 6004, École Centrale de Nantes, Nantes, France.
    Background: The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. Read More

    Detangling PPI networks to uncover functionally meaningful clusters.
    BMC Syst Biol 2018 Mar 21;12(Suppl 3):24. Epub 2018 Mar 21.
    Department of Computer Science, Tufts University, Medford, 02155, MA, USA.
    Background: Decomposing a protein-protein interaction network (PPI network) into non-overlapping clusters or communities, sometimes called "network modules," is an important way to explore functional roles of sets of genes. When the method to accomplish this decomposition is solely based on purely graph-theoretic measures of the interconnection structure of the network, this is often called unsupervised clustering or community detection. In this study, we compare unsupervised computational methods for decomposing a PPI network into non-overlapping modules. Read More

    Intrinsically Bayesian robust classifier for single-cell gene expression trajectories in gene regulatory networks.
    BMC Syst Biol 2018 Mar 21;12(Suppl 3):23. Epub 2018 Mar 21.
    Department of Electrical and Computer Engineering, Texas A&M University, College Station, 77843, TX, USA.
    Background: Expression-based phenotype classification using either microarray or RNA-Seq measurements suffers from a lack of specificity because pathway timing is not revealed and expressions are averaged across groups of cells. This paper studies expression-based classification under the assumption that single-cell measurements are sampled at a sufficient rate to detect regulatory timing. Thus, observations are expression trajectories. Read More

    Three-dimensional experiments and individual based simulations show that cell proliferation drives melanoma nest formation in human skin tissue.
    BMC Syst Biol 2018 Mar 27;12(1):34. Epub 2018 Mar 27.
    Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Kelvin Grove, 4059, Australia.
    Background: Melanoma can be diagnosed by identifying nests of cells on the skin surface. Understanding the processes that drive nest formation is important as these processes could be potential targets for new cancer drugs. Cell proliferation and cell migration are two potential mechanisms that could conceivably drive melanoma nest formation. Read More

    SPSNet: subpopulation-sensitive network-based analysis of heterogeneous gene expression data.
    BMC Syst Biol 2018 Mar 19;12(Suppl 2):28. Epub 2018 Mar 19.
    School of Computing, National University of Singapore, 13 Computing Drive, Singapore, 117417, Singapore.
    Background: Transcriptomic datasets often contain undeclared heterogeneity arising from biological variation such as diversity of disease subtypes, treatment subgroups, time-series gene expression, nested experimental conditions, as well as technical variation due to batch effects, platform differences in integrated meta-analyses, etc. However, current analysis approaches are primarily designed to handle comparisons between experimental conditions represented by homogeneous samples, thus precluding the discovery of underlying subphenotypes. Unsupervised methods for subtype identification are typically based on individual gene level analysis, which often result in irreproducible gene signatures for potential subtypes. Read More

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