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    1773 results match your criteria BMC Systems Biology [Journal]

    1 OF 36

    Modeling the therapeutic efficacy of NFκB synthetic decoy oligodeoxynucleotides (ODNs).
    BMC Syst Biol 2018 Jan 30;12(1). Epub 2018 Jan 30.
    Center for Theoretical Biological Physics, Rice University, Houston, 77005, TX, USA.
    Background: Transfection of NF κB synthetic decoy Oligodeoxynucleotides (ODNs) has been proposed as a promising therapeutic strategy for a variety of diseases arising from constitutive activation of the eukaryotic transcription factor NF κB. The decoy approach faces some limitations under physiological conditions notably nuclease-induced degradation.

    Results: In this work, we show how a systems pharmacology model of NF κB regulatory networks displaying oscillatory temporal dynamics, can be used to predict quantitatively the dependence of therapeutic efficacy of NF κB synthetic decoy ODNs on dose, unbinding kinetic rates and nuclease-induced degradation rates. Read More

    MDD-carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):137. Epub 2017 Dec 21.
    Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, city, 320, Taiwan.
    Background: Carbonylation, which takes place through oxidation of reactive oxygen species (ROS) on specific residues, is an irreversibly oxidative modification of proteins. It has been reported that the carbonylation is related to a number of metabolic or aging diseases including diabetes, chronic lung disease, Parkinson's disease, and Alzheimer's disease. Due to the lack of computational methods dedicated to exploring motif signatures of protein carbonylation sites, we were motivated to exploit an iterative statistical method to characterize and identify carbonylated sites with motif signatures. Read More

    Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):125. Epub 2017 Dec 21.
    Department of Electrical/Electronic and Computer Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 44610, Republic of Korea.
    Background: Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. Read More

    Computational analysis reveals the coupling between bistability and the sign of a feedback loop in a TGF-β1 activation model.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):136. Epub 2017 Dec 21.
    Computational and Systems Biology Program, Singapore-MIT Alliance, Singapore, 117576, Singapore.
    Background: Bistable behaviors are prevalent in cell signaling and can be modeled by ordinary differential equations (ODEs) with kinetic parameters. A bistable switch has recently been found to regulate the activation of transforming growth factor-β1 (TGF-β1) in the context of liver fibrosis, and an ordinary differential equation (ODE) model was published showing that the net activation of TGF-β1 depends on the balance between two antagonistic sub-pathways.

    Results: Through modeling the effects of perturbations that affect both sub-pathways, we revealed that bistability is coupled with the signs of feedback loops in the model. Read More

    Integrating transcriptional activity in genome-scale models of metabolism.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):134. Epub 2017 Dec 21.
    UMR 8030 Génomique Métabolique / Laboratoire iSSB CEA-CNRS-UEVE, Genopole campus 1, 5 rue Henri Desbruères, Cedex Évry, 91030, France.
    Background: Genome-scale metabolic models provide an opportunity for rational approaches to studies of the different reactions taking place inside the cell. The integration of these models with gene regulatory networks is a hot topic in systems biology. The methods developed to date focus mostly on resolving the metabolic elements and use fairly straightforward approaches to assess the impact of genome expression on the metabolic phenotype. Read More

    Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):130. Epub 2017 Dec 21.
    Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr, Ann Arbor, MI, 48109, USA.
    Background: Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. Read More

    Constraint-based perturbation analysis with cluster Newton method: a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):129. Epub 2017 Dec 21.
    Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuda-cho, Midori-ku, Yokohama-shi, Kanagawa, 226-8503, Japan.
    Background: Drug development considering individual varieties among patients becomes crucial to improve clinical development success rates and save healthcare costs. As a useful tool to predict individual phenomena and correlations among drug characteristics and individual varieties, recently, whole-body physiologically based pharmacokinetic (WB- PBPK) models are getting more attention. WB-PBPK models generally have a lot of drug-related parameters that need to be estimated, and the estimations are difficult because the observed data are limited. Read More

    CPredictor3.0: detecting protein complexes from PPI networks with expression data and functional annotations.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):135. Epub 2017 Dec 21.
    Department of Computer Science and Technology, Tongji University, Shanghai, 201804, China.
    Background: Effectively predicting protein complexes not only helps to understand the structures and functions of proteins and their complexes, but also is useful for diagnosing disease and developing new drugs. Up to now, many methods have been developed to detect complexes by mining dense subgraphs from static protein-protein interaction (PPI) networks, while ignoring the value of other biological information and the dynamic properties of cellular systems.

    Results: In this paper, based on our previous works CPredictor and CPredictor2. Read More

    Construction and analysis of gene-gene dynamics influence networks based on a Boolean model.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):133. Epub 2017 Dec 21.
    Department of Electrical/Electronic and Computer Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 44610, Republic of Korea.
    Background: Identification of novel gene-gene relations is a crucial issue to understand system-level biological phenomena. To this end, many methods based on a correlation analysis of gene expressions or structural analysis of molecular interaction networks have been proposed. They have a limitation in identifying more complicated gene-gene dynamical relations, though. Read More

    A polynomial based model for cell fate prediction in human diseases.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):126. Epub 2017 Dec 21.
    Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
    Background: Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development.

    Results: In this study, we proposed a polynomial based model to predict cell fate. Read More

    Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):132. Epub 2017 Dec 21.
    Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
    Background: Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. Read More

    Hadamard Kernel SVM with applications for breast cancer outcome predictions.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):138. Epub 2017 Dec 21.
    Department of Mathematics, School of Information, Renmin University of China, No.59 Zhong Guan Cun Avenue, Hai Dian District, Beijing, 100872, China.
    Background: Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Read More

    A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):127. Epub 2017 Dec 21.
    School of Information & Electronic Engineering, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou, 310018, China.
    Background: In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. Read More

    Identification of natural antimicrobial peptides from bacteria through metagenomic and metatranscriptomic analysis of high-throughput transcriptome data of Taiwanese oolong teas.
    BMC Syst Biol 2017 Dec 21;11(Suppl 7):131. Epub 2017 Dec 21.
    Department of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
    Background: Anti-microbial peptides (AMPs), naturally encoded by genes and generally containing 12-100 amino acids, are crucial components of the innate immune system and can protect the host from various pathogenic bacteria and viruses. In recent years, the widespread use of antibiotics has resulted in the rapid growth of antibiotic-resistant microorganisms that often induce critical infection and pathogenesis. Recently, the advent of high-throughput technologies has led molecular biology into a data surge in both the amount and scope of data. Read More

    Meta-analysis of human gene expression in response to Mycobacterium tuberculosis infection reveals potential therapeutic targets.
    BMC Syst Biol 2018 Jan 10;12(1). Epub 2018 Jan 10.
    Computational Biology, Target Sciences, GlaxoSmithKline (GSK) R & D, Collegeville, PA, 19426, USA.
    Background: With the global emergence of multi-drug resistant strains of Mycobacterium tuberculosis, new strategies to treat tuberculosis are urgently needed such as therapeutics targeting potential human host factors.

    Results: Here we performed a statistical meta-analysis of human gene expression in response to both latent and active pulmonary tuberculosis infections from nine published datasets. We found 1655 genes that were significantly differentially expressed during active tuberculosis infection. Read More

    Dengue virus causes changes of MicroRNA-genes regulatory network revealing potential targets for antiviral drugs.
    BMC Syst Biol 2018 Jan 4;12(1). Epub 2018 Jan 4.
    College of Life Science, Northwest A & F University, Yangling, Shaanxi, 712100, China.
    Background: Dengue virus (DENV) is an increasing global health threat and associated with induction of both a long-lived protective immune response and immune-suppression. So far, the potency of treatment of DENV via antiviral drugs is still under investigation. Recently, increasing evidences suggest the potential role of microRNAs (miRNAs) in regulating DENV. Read More

    Identifying drug-pathway association pairs based on L-integrative penalized matrix decomposition.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):119. Epub 2017 Dec 14.
    School of Information Science and Engineering, Qufu Normal University, Rizhao, China.
    Background: Traditional drug identification methods follow the "one drug-one target" thought. But those methods ignore the natural characters of human diseases. To overcome this limitation, many identification methods of drug-pathway association pairs have been developed, such as the integrative penalized matrix decomposition (iPaD) method. Read More

    A unified frame of predicting side effects of drugs by using linear neighborhood similarity.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):101. Epub 2017 Dec 14.
    School of Computer, Wuhan University, Wuhan, 430072, China.
    Background: Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. Read More

    Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):115. Epub 2017 Dec 14.
    School of Mathematics and Statistics, Xi'An Jiaotong University, No.28 West Xianning Road, Xi'An, 710049, China.
    Background: Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applications do not produce positive semi-definite kernels.

    Methods: We propose projection method by constructing projection matrix on indefinite kernels. Read More

    A geometric method for contour extraction of Drosophila embryos.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):102. Epub 2017 Dec 14.
    Cisco School of Informatics, Guangdong University of Foreign Studies, Guangzhou, 510006, People's Republic of China.
    Background: High resolution images of Drosophila embryos in their developmental stages contain rich spatial and temporal information of gene expression. Automatic extraction of the contour of an embryo of interest in an embryonic image is a critical step of a computational system used to discover gene-gene interaction on Drosophila.

    Results: We propose a geometric method for contour extraction of Drosophila embryos. Read More

    Model checking optimal finite-horizon control for probabilistic gene regulatory networks.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):104. Epub 2017 Dec 14.
    Department of Mathematics and Statistics, University of Calgary, Calgary, Canada.
    Background: Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. Read More

    Reconstructing evolutionary trees in parallel for massive sequences.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):100. Epub 2017 Dec 14.
    State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
    Background: Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Read More

    Mining significant high utility gene regulation sequential patterns.
    BMC Syst Biol 2017 Dec 14;11(Suppl 6):109. Epub 2017 Dec 14.
    Department of Electrical Engineering and Computer Science, York University, Keele Street, Toronto, Canada.
    Background: Mining frequent gene regulation sequential patterns in time course microarray datasets is an important mining task in bioinformatics. Although finding such patterns are of paramount important for studying a disease, most existing work do not consider gene-disease association during gene regulation sequential pattern discovery. Moreover, they consider more absent/existence effects of genes during the mining process than taking the degrees of genes expression into account. Read More

    Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.
    BMC Syst Biol 2018 Jan 2;12(1). Epub 2018 Jan 2.
    Department of Biosciences, Durham University, South Road, Durham, DH1 3LE, UK.
    Background: Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. Read More

    Use of transcriptomic data for extending a model of the AppA/PpsR system in Rhodobacter sphaeroides.
    BMC Syst Biol 2017 Dec 28;11(1):146. Epub 2017 Dec 28.
    Department of Biochemistry, University of Oxford, South Parks Road, Oxford, UK.
    Background: Photosynthetic (PS) gene expression in Rhodobacter sphaeroides is regulated in response to changes in light and redox conditions mainly by PrrB/A, FnrL and AppA/PpsR systems. The PrrB/A and FnrL systems activate the expression of them under anaerobic conditions while the AppA/PpsR system represses them under aerobic conditions. Recently, two mathematical models have been developed for the AppA/PpsR system and demonstrated how the interaction between AppA and PpsR could lead to a phenotype in which PS genes are repressed under semi-aerobic conditions. Read More

    Analysis of the main active ingredients and bioactivities of essential oil from Osmanthus fragrans Var. thunbergii using a complex network approach.
    BMC Syst Biol 2017 Dec 28;11(1):144. Epub 2017 Dec 28.
    Shaanxi Key Laboratory of Phytochemistry, College of Chemistry and Chemical Engineering, Baoji University of Arts and Sciences, Baoji, Shaanxi, 721013, China.
    Background: Osmanthus fragrans has been used as folk medicine for thousands of years. The extracts of Osmanthus fragrans flowers were reported to have various bioactivities including free radical scavenging, anti-inflammation, neuroprotection and antitumor effects. However, there is still lack of knowledge about its essential oil. Read More

    Microbiota dysbiosis in inflammatory bowel diseases: in silico investigation of the oxygen hypothesis.
    BMC Syst Biol 2017 Dec 28;11(1):145. Epub 2017 Dec 28.
    Department of Chemical Engineering and the Institute for Applied Life Sciences, University of Massachusetts, 140 Thatcher Way, Amherst, 01003, MA, USA.
    Background: Inflammatory bowel diseases (IBD), which include ulcerative colitis and Crohn's disease, cause chronic inflammation of the digestive tract in approximately 1.6 million Americans. A signature of IBD is dysbiosis of the gut microbiota marked by a significant reduction of obligate anaerobes and a sharp increase in facultative anaerobes. Read More

    OptPipe - a pipeline for optimizing metabolic engineering targets.
    BMC Syst Biol 2017 Dec 21;11(1):143. Epub 2017 Dec 21.
    IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal.
    Background: We propose OptPipe - a Pipeline for Optimizing Metabolic Engineering Targets, based on a consensus approach. The method generates consensus hypotheses for metabolic engineering applications by combining several optimization solutions obtained from distinct algorithms. The solutions are ranked according to several objectives, such as biomass and target production, by using the rank product tests corrected for multiple comparisons. Read More

    Systems healthcare: a holistic paradigm for tomorrow.
    BMC Syst Biol 2017 Dec 19;11(1):142. Epub 2017 Dec 19.
    Department of Neurology, School of Medicine, Irvine, USA.
    Systems healthcare is a holistic approach to health premised on systems biology and medicine. The approach integrates data from molecules, cells, organs, the individual, families, communities, and the natural and man-made environment. Both extrinsic and intrinsic influences constantly challenge the biological networks associated with wellness. Read More

    Identification of regulatory modules in genome scale transcription regulatory networks.
    BMC Syst Biol 2017 Dec 15;11(1):140. Epub 2017 Dec 15.
    Department of Crop & Soil Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.
    Background: In gene regulatory networks, transcription factors often function as co-regulators to synergistically induce or inhibit expression of their target genes. However, most existing module-finding algorithms can only identify densely connected genes but not co-regulators in regulatory networks.

    Methods: We have developed a new computational method, CoReg, to identify transcription co-regulators in large-scale regulatory networks. Read More

    Linking physiologically-based pharmacokinetic and genome-scale metabolic networks to understand estradiol biology.
    BMC Syst Biol 2017 Dec 15;11(1):141. Epub 2017 Dec 15.
    School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK.
    Background: Estrogen is a vital hormone that regulates many biological functions within the body. These include roles in the development of the secondary sexual organs in both sexes, plus uterine angiogenesis and proliferation during the menstrual cycle and pregnancy in women. The varied biological roles of estrogens in human health also make them a therapeutic target for contraception, mitigation of the adverse effects of the menopause, and treatment of estrogen-responsive tumours. Read More

    Estimating drivers of cell state transitions using gene regulatory network models.
    BMC Syst Biol 2017 Dec 13;11(1):139. Epub 2017 Dec 13.
    Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, 02115, MA, USA.
    Background: Specific cellular states are often associated with distinct gene expression patterns. These states are plastic, changing during development, or in the transition from health to disease. One relatively simple extension of this concept is to recognize that we can classify different cell-types by their active gene regulatory networks and that, consequently, transitions between cellular states can be modeled by changes in these underlying regulatory networks. Read More

    A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.
    BMC Syst Biol 2017 Dec 11;11(1):124. Epub 2017 Dec 11.
    Department of Biological Sciences, University of Delaware, Newark, DE, 19716, USA.
    Background: Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e. Read More

    GoldenPiCS: a Golden Gate-derived modular cloning system for applied synthetic biology in the yeast Pichia pastoris.
    BMC Syst Biol 2017 Dec 8;11(1):123. Epub 2017 Dec 8.
    Department of Biotechnology, BOKU University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria.
    Background: State-of-the-art strain engineering techniques for the host Pichia pastoris (syn. Komagataella spp.) include overexpression of homologous and heterologous genes, and deletion of host genes. Read More

    Gene gravity-like algorithm for disease gene prediction based on phenotype-specific network.
    BMC Syst Biol 2017 Dec 6;11(1):121. Epub 2017 Dec 6.
    Institute of Interdisciplinary Complex Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
    Background: Polygenic diseases are usually caused by the dysfunction of multiple genes. Unravelling such disease genes is crucial to fully understand the genetic landscape of diseases on molecular level. With the advent of 'omic' data era, network-based methods have prominently boosted disease gene discovery. Read More

    A framework to find the logic backbone of a biological network.
    BMC Syst Biol 2017 Dec 6;11(1):122. Epub 2017 Dec 6.
    Department of Physics, The Pennsylvania State University, University Park, 16802, PA, USA.
    Background: Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. Read More

    Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A.
    BMC Syst Biol 2017 Dec 4;11(1):120. Epub 2017 Dec 4.
    Faculty of Maths & IT, Royal Thimphu College, Nagbiphu, Thimphu, 1122, Bhutan.
    Background: Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Read More

    Designing synthetic networks in silico: a generalised evolutionary algorithm approach.
    BMC Syst Biol 2017 Dec 2;11(1):118. Epub 2017 Dec 2.
    Laboratory of Systems & Synthetic Biology, Wageningen UR, PO Box 8033, Wageningen, 6700EJ, The Netherlands.
    Background: Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. Read More

    Genetic toggle switch controlled by bacterial growth rate.
    BMC Syst Biol 2017 Dec 2;11(1):117. Epub 2017 Dec 2.
    Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawińskiego 5B, Warsaw, 02-106, Poland.
    Background: In favorable conditions bacterial doubling time is less than 20 min, shorter than DNA replication time. In E. coli a single round of genome replication lasts about 40 min and it must be accomplished about 20 min before cell division. Read More

    Synthetic enhancer design by in silico compensatory evolution reveals flexibility and constraint in cis-regulation.
    BMC Syst Biol 2017 Nov 29;11(1):116. Epub 2017 Nov 29.
    Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Zoology 111, 1101 E 57th St, Chicago, 60637, Illinois, USA.
    Background: Models that incorporate specific chemical mechanisms have been successful in describing the activity of Drosophila developmental enhancers as a function of underlying transcription factor binding motifs. Despite this, the minimum set of mechanisms required to reconstruct an enhancer from its constituent parts is not known. Synthetic biology offers the potential to test the sufficiency of known mechanisms to describe the activity of enhancers, as well as to uncover constraints on the number, order, and spacing of motifs. Read More

    A multiscale modeling study of particle size effects on the tissue penetration efficacy of drug-delivery nanoparticles.
    BMC Syst Biol 2017 Nov 25;11(1):113. Epub 2017 Nov 25.
    Department of Chemical and Biochemical Engineering, University of Missouri Science and Technology, Rolla, Missouri, USA.
    Background: Particle size is a key parameter for drug-delivery nanoparticle design. It is believed that the size of a nanoparticle may have important effects on its ability to overcome the transport barriers in biological tissues. Nonetheless, such effects remain poorly understood. Read More

    MitoCore: a curated constraint-based model for simulating human central metabolism.
    BMC Syst Biol 2017 Nov 25;11(1):114. Epub 2017 Nov 25.
    Medical Research Council Mitochondrial Biology Unit, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0XY, UK.
    Background: The complexity of metabolic networks can make the origin and impact of changes in central metabolism occurring during diseases difficult to understand. Computer simulations can help unravel this complexity, and progress has advanced in genome-scale metabolic models. However, many models produce unrealistic results when challenged to simulate abnormal metabolism as they include incorrect specification and localisation of reactions and transport steps, incorrect reaction parameters, and confounding of prosthetic groups and free metabolites in reactions. Read More

    Genome-wide analysis of E. coli cell-gene interactions.
    BMC Syst Biol 2017 Nov 23;11(1):112. Epub 2017 Nov 23.
    California Institute for Quantitative Biosciences, University of California-Berkeley, Berkeley, CA, 94720, USA.
    Background: The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. Read More

    Multiscale positive feedbacks contribute to unidirectional gastric disease progression induced by helicobacter pylori infection.
    BMC Syst Biol 2017 Nov 22;11(1):111. Epub 2017 Nov 22.
    Department of Molecular and Cellular Physiology, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
    Background: Helicobacter Pylori (HP) is the most common risk factor for gastric cancer. Nearly half the world's population is infected with HP, but only a small percentage of those develop significant pathology. The bacteria itself does not directly cause cancer; rather it promotes an environment that is conducive to tumor formation. Read More

    Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes.
    BMC Syst Biol 2017 Nov 22;11(1):110. Epub 2017 Nov 22.
    Computer Engineering, Antalya Bilim University, Antalya, Turkey.
    Background: Identification of driver genes related to certain types of cancer is an important research topic. Several systems biology approaches have been suggested, in particular for the identification of breast cancer (BRCA) related genes. Such approaches usually rely on differential gene expression and/or mutational landscape data. Read More

    A computational study of the inhibition mechanisms of P-glycoprotein mediated paclitaxel efflux by kinase inhibitors.
    BMC Syst Biol 2017 Nov 21;11(1):108. Epub 2017 Nov 21.
    Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA.
    Background: Drug resistance mediated by P-glycoprotein (P-gp) renders many cancer therapies ineffective. One P-gp substrate is the widely used chemotherapy drug paclitaxel. Co-administration of paclitaxel and another drug that inhibits P-gp may enhance the therapeutic effectiveness of paclitaxel by preventing its efflux from tumor cells. Read More

    Inferring gene regulatory networks from single-cell data: a mechanistic approach.
    BMC Syst Biol 2017 Nov 21;11(1):105. Epub 2017 Nov 21.
    Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 allée d'Italie Site Jacques Monod, Lyon, F-69007, France.
    Background: The recent development of single-cell transcriptomics has enabled gene expression to be measured in individual cells instead of being population-averaged. Despite this considerable precision improvement, inferring regulatory networks remains challenging because stochasticity now proves to play a fundamental role in gene expression. In particular, mRNA synthesis is now acknowledged to occur in a highly bursty manner. Read More

    Monitoring of nutrient limitation in growing E. coli: a mathematical model of a ppGpp-based biosensor.
    BMC Syst Biol 2017 Nov 21;11(1):106. Epub 2017 Nov 21.
    Institute of Molecular, Cell and Systems Biology, University of Glasgow, Glasgow, Scotland, UK.
    Background: E. coli can be used as bacterial cell factories for production of biofuels and other useful compounds. The efficient production of the desired products requires careful monitoring of growth conditions and the optimization of metabolic fluxes. Read More

    Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection.
    BMC Syst Biol 2017 Nov 21;11(1):107. Epub 2017 Nov 21.
    Grupo de Bioprocesos, Departamento de Ingeniería Química, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia.
    Background: Up to date, Mycobacterium tuberculosis (Mtb) remains as the worst intracellular killer pathogen. To establish infection, inside the granuloma, Mtb reprograms its metabolism to support both growth and survival, keeping a balance between catabolism, anabolism and energy supply. Mtb knockouts with the faculty of being essential on a wide range of nutritional conditions are deemed as target candidates for tuberculosis (TB) treatment. Read More

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