IEEE life sciences letters最新文献_第2页

Multiscale Metabolic Modeling Approach for Predicting Blood Alcohol Concentration 预测血液酒精浓度的多尺度代谢建模方法

IEEE life sciences letters Pub Date : 2016-12-01 DOI: 10.1109/LLS.2016.2644647

M. K. Toroghi, W. R. Cluett, R. Mahadevan

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引用次数: 7

Multiscale Metabolic Modeling Approach for Predicting Blood Alcohol Concentration 预测血液酒精浓度的多尺度代谢建模方法

IEEE life sciences letters Pub Date : 2016-12-01 DOI: 10.1109/LLS.2016.2644647

Masood Khaksar Toroghi;William R. Cluett;Radhakrishnan Mahadevan

{"title":"Multiscale Metabolic Modeling Approach for Predicting Blood Alcohol Concentration","authors":"Masood Khaksar Toroghi;William R. Cluett;Radhakrishnan Mahadevan","doi":"10.1109/LLS.2016.2644647","DOIUrl":"https://doi.org/10.1109/LLS.2016.2644647","url":null,"abstract":"Alcohol is one of the most widely consumed and abused substances, and is a major factor in many alcohol-related diseases, incidents of impaired driving, and crimes. In this letter, we develop a mechanistic model for alcohol metabolism in the human body based on the dynamic parsimonious flux balance analysis technique. The developed whole body alcohol metabolic model contains two main mechanisms for ethanol metabolism in the body, namely, oxidative and non-oxidative mechanisms. The model is able to demonstrate the effect of variations in biochemical kinetics associated with the alcohol dehydrogenase enzyme, gender differences, physiological properties of the human body such as age, weight, and height, and the meal effect on the alcohol clearance from the body. Simulation results show that the model predictions are consistent with in vivo studies. The results from this letter indicate that the proposed metabolic modeling approach may open the door to new opportunities in the area of metabolic nutrition research and personalized medicine since it accounts for physiological properties and biochemical information related to the human body.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 4","pages":"59-62"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2644647","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49986488","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: 7

A Multimetric Evaluation of Stratified Random Sampling for Classification: A Case Study 分层随机抽样分类的多度量评价:一个案例研究

IEEE life sciences letters Pub Date : 2016-10-05 DOI: 10.1109/LLS.2016.2615086

Gunjan Thakur, Bernie J. Daigle, Meng Qian, Kelsey R. Dean, Yuanyang Zhang, Ruoting Yang, Taek‐Kyun Kim, Xiaogang Wu, Meng Li, Inyoul Y. Lee, L. Petzold, Francis J. Doyle

{"title":"A Multimetric Evaluation of Stratified Random Sampling for Classification: A Case Study","authors":"Gunjan Thakur, Bernie J. Daigle, Meng Qian, Kelsey R. Dean, Yuanyang Zhang, Ruoting Yang, Taek‐Kyun Kim, Xiaogang Wu, Meng Li, Inyoul Y. Lee, L. Petzold, Francis J. Doyle","doi":"10.1109/LLS.2016.2615086","DOIUrl":"https://doi.org/10.1109/LLS.2016.2615086","url":null,"abstract":"Accurate classification of biological phenotypes is an essential task for medical decision making. The selection of subjects for classifier training and validation sets is a crucial step within this task. To evaluate the impact of two approaches for subject selection—randomization and clinical balancing, we applied six classification algorithms to a highly replicated publicly available breast cancer data set. Using six performance metrics, we demonstrate that clinical balancing improves both training and validation performance for all methods on average. We also observed a smaller discrepancy between training and validation performance. Furthermore, a simple analytical argument is presented which suggests that we need only two metrics from the class of metrics based on the entries of the confusion matrix. In light of our results, we recommend: 1) clinical balancing of training and validation data to improve signal-to-noise ratio and 2) the use of multiple classification algorithms and evaluation metrics for a comprehensive evaluation of the decision making process.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 1","pages":"43-46"},"PeriodicalIF":0.0,"publicationDate":"2016-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2615086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62509475","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: 4

A Multimetric Evaluation of Stratified Random Sampling for Classification: A Case Study 分层随机抽样分类的多度量评价:一个案例研究

IEEE life sciences letters Pub Date : 2016-10-05 DOI: 10.1109/LLS.2016.2615086

Gunjan S. Thakur;Bernie J. Daigle;Meng Qian;Kelsey R. Dean;Yuanyang Zhang;Ruoting Yang;Taek-Kyun Kim;Xiaogang Wu;Meng Li;Inyoul Lee;Linda R. Petzold;Francis J. Doyle

{"title":"A Multimetric Evaluation of Stratified Random Sampling for Classification: A Case Study","authors":"Gunjan S. Thakur;Bernie J. Daigle;Meng Qian;Kelsey R. Dean;Yuanyang Zhang;Ruoting Yang;Taek-Kyun Kim;Xiaogang Wu;Meng Li;Inyoul Lee;Linda R. Petzold;Francis J. Doyle","doi":"10.1109/LLS.2016.2615086","DOIUrl":"https://doi.org/10.1109/LLS.2016.2615086","url":null,"abstract":"Accurate classification of biological phenotypes is an essential task for medical decision making. The selection of subjects for classifier training and validation sets is a crucial step within this task. To evaluate the impact of two approaches for subject selection-randomization and clinical balancing, we applied six classification algorithms to a highly replicated publicly available breast cancer data set. Using six performance metrics, we demonstrate that clinical balancing improves both training and validation performance for all methods on average. We also observed a smaller discrepancy between training and validation performance. Furthermore, a simple analytical argument is presented which suggests that we need only two metrics from the class of metrics based on the entries of the confusion matrix. In light of our results, we recommend: 1) clinical balancing of training and validation data to improve signal-to-noise ratio and 2) the use of multiple classification algorithms and evaluation metrics for a comprehensive evaluation of the decision making process.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 4","pages":"43-46"},"PeriodicalIF":0.0,"publicationDate":"2016-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2615086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49986484","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: 5

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 : 2016-10-04 DOI: 10.1109/LLS.2016.2615091

M. Ahsen, H. Ozbay, S. Niculescu

引用次数: 4

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

IEEE life sciences letters Pub Date : 2016-10-04 DOI: 10.1109/LLS.2016.2615089

S. Waldherr, Philip Trennt, M. Hussain

引用次数: 2

Regularization Techniques to Overcome Overparameterization of Complex Biochemical Reaction Networks 克服复杂生化反应网络过度参数化的正则化技术

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2016.2646498

Daniel P. Howsmon;Juergen Hahn

引用次数: 9

The Cell as a Decision-Making Unit 作为决策单位的细胞

IEEE life sciences letters Pub Date : 2016-09-01 DOI: 10.1109/LLS.2016.2644648

Lorenzo Castelli;Raffaele Pesenti;Daniel Segrè

引用次数: 4

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, M. Birtwistle, C. Belta, A. 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, T. Wood, Z. 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, T. Wood, Z. 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 1","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":"62509739","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