IEEE life sciences letters最新文献_第3页

GillesPy: A Python Package for Stochastic Model Building and Simulation GillesPy:一个用于随机模型构建和仿真的Python包

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2017.2652448

John H. Abel;Brian Drawert;Andreas Hellander;Linda R. Petzold

引用次数: 41

Guest Editorial: Special Issue on the Foundations of Systems Biology in Engineering (FOSBE) 客座社论:工程系统生物学基础特刊(FOSBE)

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2016.2646560

Robert S. Parker

{"title":"Guest Editorial: Special Issue on the Foundations of Systems Biology in Engineering (FOSBE)","authors":"Robert S. Parker","doi":"10.1109/LLS.2016.2646560","DOIUrl":"https://doi.org/10.1109/LLS.2016.2646560","url":null,"abstract":"The complete sequencing of the human genome has undoubtedly advanced the study of biology and the practice of medicine, including some dramatic and rapid advances in human health. This progress has been slowed, however, by the challenge of understanding how the genetic players, and their regulation, interact to yield systemic responses to disease and treatment. Taking a puzzle as an analogy for life, the landmark achievement of identifying the human genome provided a list of the possible puzzle pieces, but it did not provide the completed picture on the cover. The search since has focused on the relationships between this genomic information and the (individual or patient) systemic response or function—the “omics” efforts in mapping proteins (proteomics) and metabolites (metabolomics). The primary avenues in this search are: 1) defining the causal connections between the plethora of transcriptional, protein, and metabolite players; 2) linking these microscale networks to system-level response; and 3) capturing the dynamics of the system in response to changes at lower scales. The fields of systems biology, and its translational science counterpart systems medicine, have emerged as the bridge between reductionist molecular and cellular biology approaches and the systems-level understanding required to use this knowledge to advance the human condition.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 3","pages":"17-18"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2646560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49909175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Temporal Logic Inference Approach for Model Discrimination 模型判别的时间逻辑推理方法

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2016.2644646

Zhe Xu;Marc Birtwistle;Calin Belta;Agung Julius

引用次数: 18

A Genome-Scale Modeling Approach to Investigate the Antibiotics-Triggered Perturbation in the Metabolism of Pseudomonas aeruginosa 研究抗生素引发的铜绿假单胞菌代谢扰动的基因组尺度建模方法

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2017.2652473

Zhaobin Xu;Nicholas Ribaudo;Xianhua Li;Thomas K. Wood;Zuyi Huang

{"title":"A Genome-Scale Modeling Approach to Investigate the Antibiotics-Triggered Perturbation in the Metabolism of Pseudomonas aeruginosa","authors":"Zhaobin Xu;Nicholas Ribaudo;Xianhua Li;Thomas K. Wood;Zuyi Huang","doi":"10.1109/LLS.2017.2652473","DOIUrl":"https://doi.org/10.1109/LLS.2017.2652473","url":null,"abstract":"Recent studies indicate that pretreating microorganisms with ribosome-targeting antibiotics may promote a transition in the microbial phenotype, such as the formation of persister cells; i.e., those cells that survive antibiotic treatment by becoming metabolically dormant. In this letter, we developed the first genome-scale modeling approach to systematically investigate the influence of ribosome-targeting antibiotics on the metabolism of Pseudomonas aeruginosa. An approach for integrating gene expression data with metabolic networks was first developed to identify the metabolic reactions whose fluxes were positively correlated with gene activation levels. The fluxes of these reactions were further constrained via a flux balance analysis to mimic the inhibition of antibiotics on microbial metabolism. It was found that some of metabolic reactions with large flux change, including metabolic reactions for homoserine metabolism, the production of 2-heptyl-4-quinolone, and isocitrate lyase, were confirmed by existing experimental data for their important role in promoting persister cell formation. Metabolites with large exchange-rate change, such as acetate, agmatine, and oxoglutarate, were found important for persister cell formation in previous experiments. The predicted results on the flux change triggered by ribosome-targeting antibiotics can be used to generate hypotheses for future experimental design to combat antibiotic-resistant pathogens.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 3","pages":"39-42"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2017.2652473","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49909174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Conditions for Cell Size Homeostasis: A Stochastic Hybrid System Approach 细胞大小稳态的条件:一种随机混合系统方法

IEEE life sciences letters Pub Date : 2016-06-02 DOI: 10.1109/LLS.2016.2646383

C. A. Vargas-Garcia, Mohammad Soltani, Abhyudai Singh

{"title":"Conditions for Cell Size Homeostasis: A Stochastic Hybrid System Approach","authors":"C. A. Vargas-Garcia, Mohammad Soltani, Abhyudai Singh","doi":"10.1109/LLS.2016.2646383","DOIUrl":"https://doi.org/10.1109/LLS.2016.2646383","url":null,"abstract":"How isogenic cell populations maintain size homeostasis, i.e., a narrow distribution of cell size, is an intriguing fundamental problem. We model cell size using a stochastic hybrid system, where a cell grows exponentially in size (volume) over time and probabilistic division events are triggered at discrete-time intervals. Moreover, whenever division occurs, size is randomly partitioned among daughter cells. We first consider a scenario where a timer (cell-cycle clock) that measures the time elapsed since the last division event regulates both the cellular growth and division rates. The analysis reveals that such a timer-controlled system cannot achieve size homeostasis, in the sense that the cell-to-cell size variation grows unboundedly with time. To explore biologically meaningful mechanisms for controlling size, we consider two classes of regulation: a size-dependent growth rate and a size-dependent division rate. Our results show that these strategies can provide bounded intercellular variation in cell size and exact mathematical conditions on the form of regulation needed for size homeostasis are derived. Different known forms of size control strategies, such as the adder and the sizer, are shown to be consistent with these results. Finally, we discuss how organisms ranging from bacteria to mammalian cells have adopted different control approaches for maintaining size homeostasis.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 1","pages":"47-50"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2646383","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62509678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 45

Analysis of a Gene Regulatory Network Model With Time Delay Using the Secant Condition 用割线条件分析具有时滞的基因调控网络模型

IEEE life sciences letters Pub Date : 2016-06-01 DOI: 10.1109/LLS.2016.2615091

Mehmet Eren Ahsen;Hitay Özbay;Silviu-Iulian Niculescu

引用次数: 4

Testing the Pattern of AKT Activation by Variational Parameter Estimation 用变分参数估计法检测AKT的激活模式

IEEE life sciences letters Pub Date : 2016-06-01 DOI: 10.1109/LLS.2016.2615081

Daniel Kaschek;Frauke Henjes;Max Hasmann;Ulrike Korf;Jens Timmer

{"title":"Testing the Pattern of AKT Activation by Variational Parameter Estimation","authors":"Daniel Kaschek;Frauke Henjes;Max Hasmann;Ulrike Korf;Jens Timmer","doi":"10.1109/LLS.2016.2615081","DOIUrl":"https://doi.org/10.1109/LLS.2016.2615081","url":null,"abstract":"Dynamic modeling has become one of the pillars of understanding complex biological systems from a mechanistic point of view. In particular, ordinary differential equations are frequently used to model the dynamics of the interacting states, e.g., molecular species in cell signaling pathways. The equations typically contain many unknown parameters, such as reaction rates and initial conditions, but also time-dependent parameters, i.e., input functions driving the system. Both are \u0000<italic>a priori</i>\u0000 unknown and need to be estimated from experimental, time-resolved data. Here, we discuss an application of indirect optimal control methods for input estimation and parameter estimation in the \u0000<italic>mammalian target of rapamycin</i>\u0000 (mTOR) signaling. Whereas the direct identification and quantification of different active mTOR complexes, e.g., \u0000<italic>mTOR complex</i>\u0000 \u0000<inline-formula> <tex-math>$textit {2}$ </tex-math></inline-formula>\u0000 (mTORC2), is only possible by highly challenging experiments, the mathematical framework allows to reconstruct its dynamics by solving an appropriate Euler–Lagrange equation based on Pontryagin’s maximum principle. The inherently large search space underlying this approach allows to test specific biological hypotheses about the activation of \u0000<italic>protein kinase B</i>\u0000 (AKT) by mTORC2 and to reject an alternative model with high statistical power. Hereby, we identify a minimal model that has AKT threonine phosphorylation as a prerequisite for serine phosphorylation by mTORC2. Based on this model, the activation of mTORC2 is predicted to be inhibited by drugs, targeting the receptors of the ERBB receptor family.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 2","pages":"13-16"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2615081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49947148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Hybrid Simulation of Heterogeneous Cell Populations 异质细胞群体的杂交模拟

IEEE life sciences letters Pub Date : 2016-06-01 DOI: 10.1109/LLS.2016.2615089

Steffen Waldherr;Philip Trennt;Mubashir Hussain

引用次数: 2

Testing the Pattern of AKT Activation by Variational Parameter Estimation 用变分参数估计法检测AKT的激活模式

IEEE life sciences letters Pub Date : 2016-06-01 DOI: 10.1109/LLS.2016.2615081

Daniel Kaschek, F. Henjes, M. Hasmann, U. Korf, J. Timmer

{"title":"Testing the Pattern of AKT Activation by Variational Parameter Estimation","authors":"Daniel Kaschek, F. Henjes, M. Hasmann, U. Korf, J. Timmer","doi":"10.1109/LLS.2016.2615081","DOIUrl":"https://doi.org/10.1109/LLS.2016.2615081","url":null,"abstract":"Dynamic modeling has become one of the pillars of understanding complex biological systems from a mechanistic point of view. In particular, ordinary differential equations are frequently used to model the dynamics of the interacting states, e.g., molecular species in cell signaling pathways. The equations typically contain many unknown parameters, such as reaction rates and initial conditions, but also time-dependent parameters, i.e., input functions driving the system. Both are a priori unknown and need to be estimated from experimental, time-resolved data. Here, we discuss an application of indirect optimal control methods for input estimation and parameter estimation in the mammalian target of rapamycin (mTOR) signaling. Whereas the direct identification and quantification of different active mTOR complexes, e.g., mTOR complex $textit {2}$ (mTORC2), is only possible by highly challenging experiments, the mathematical framework allows to reconstruct its dynamics by solving an appropriate Euler–Lagrange equation based on Pontryagin’s maximum principle. The inherently large search space underlying this approach allows to test specific biological hypotheses about the activation of protein kinase B (AKT) by mTORC2 and to reject an alternative model with high statistical power. Hereby, we identify a minimal model that has AKT threonine phosphorylation as a prerequisite for serine phosphorylation by mTORC2. Based on this model, the activation of mTORC2 is predicted to be inhibited by drugs, targeting the receptors of the ERBB receptor family.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 1","pages":"13-16"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2615081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62509380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Novel Digital Phantom Using an Optical Noncontact Measurement System 一种基于光学非接触测量系统的新型数字幻影

IEEE life sciences letters Pub Date : 2016-03-01 DOI: 10.1109/LLS.2016.2568259

Xiaodong Yang, A. Ren, Tianqiao Zhu, Fangming Hu

引用次数: 0