Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 49 to 60 of 1077 entries
Sorted by: Best Match Show Resources per page
Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

ACS synthetic biology

Huynh L, Tagkopoulos I.
PMID: 25916918
ACS Synth Biol. 2015 Aug 21;4(8):890-7. doi: 10.1021/sb500339k. Epub 2015 Apr 28.

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any...

Cite
Huynh L, Tagkopoulos I. Fast and Accurate Circuit Design Automation through Hierarchical Model Switching. ACS Synth Biol. 2015;4(8):890-7doi: 10.1021/sb500339k.
Huynh, L., & Tagkopoulos, I. (2015). Fast and Accurate Circuit Design Automation through Hierarchical Model Switching. ACS synthetic biology, 4(8), 890-7. https://doi.org/10.1021/sb500339k
Huynh, Linh, and Tagkopoulos, Ilias. "Fast and Accurate Circuit Design Automation through Hierarchical Model Switching." ACS synthetic biology vol. 4,8 (2015): 890-7. doi: https://doi.org/10.1021/sb500339k
Huynh L, Tagkopoulos I. Fast and Accurate Circuit Design Automation through Hierarchical Model Switching. ACS Synth Biol. 2015 Aug 21;4(8):890-7. doi: 10.1021/sb500339k. Epub 2015 Apr 28. PMID: 25916918.
Copy Download .nbib Format: NLM
The Effect of Intra- and Interspecific Competition on Coexistence in Multispecies Communities.

The American naturalist

Barabás G, J Michalska-Smith M, Allesina S.
PMID: 27322128
Am Nat. 2016 Jul;188(1):E1-E12. doi: 10.1086/686901. Epub 2016 May 23.

For two competing species, intraspecific competition must exceed interspecific competition for coexistence. To generalize this well-known criterion to multiple competing species, one must take into account both the distribution of interaction strengths and community structure. Here we derive a...

Cite
Barabás G, J Michalska-Smith M, Allesina S. The Effect of Intra- and Interspecific Competition on Coexistence in Multispecies Communities. Am Nat. 2016;188(1):E1-E12doi: 10.1086/686901.
Barabás, G., J Michalska-Smith, M., & Allesina, S. (2016). The Effect of Intra- and Interspecific Competition on Coexistence in Multispecies Communities. The American naturalist, 188(1), E1-E12. https://doi.org/10.1086/686901
Barabás, György, et al. "The Effect of Intra- and Interspecific Competition on Coexistence in Multispecies Communities." The American naturalist vol. 188,1 (2016): E1-E12. doi: https://doi.org/10.1086/686901
Barabás G, J Michalska-Smith M, Allesina S. The Effect of Intra- and Interspecific Competition on Coexistence in Multispecies Communities. Am Nat. 2016 Jul;188(1):E1-E12. doi: 10.1086/686901. Epub 2016 May 23. PMID: 27322128.
Copy Download .nbib Format: NLM
Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization.

IEEE/ACM transactions on computational biology and bioinformatics

Jiang X, Hu X, Xu W, Park EK.
PMID: 26357214
IEEE/ACM Trans Comput Biol Bioinform. 2015 Mar-Apr;12(2):254-61. doi: 10.1109/TCBB.2014.2338298.

Microbial interactions play important roles on the structure and function of complex microbial communities. With the rapid accumulation of high-throughput metagenomic or 16S rRNA sequencing data, it is possible to infer complex microbial interactions. Co-occurrence patterns of microbial species...

Cite
Jiang X, Hu X, Xu W, et al. Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM Trans Comput Biol Bioinform. 2015;12(2):254-61doi: 10.1109/TCBB.2014.2338298.
Jiang, X., Hu, X., Xu, W., & Park, E. K. (2015). Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM transactions on computational biology and bioinformatics, 12(2), 254-61. https://doi.org/10.1109/TCBB.2014.2338298
Jiang, Xingpeng, et al. "Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization." IEEE/ACM transactions on computational biology and bioinformatics vol. 12,2 (2015): 254-61. doi: https://doi.org/10.1109/TCBB.2014.2338298
Jiang X, Hu X, Xu W, Park EK. Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM Trans Comput Biol Bioinform. 2015 Mar-Apr;12(2):254-61. doi: 10.1109/TCBB.2014.2338298. PMID: 26357214.
Copy Download .nbib Format: NLM
Learning (from) the errors of a systems biology model.

Scientific reports

Engelhardt B, Frőhlich H, Kschischo M.
PMID: 26865316
Sci Rep. 2016 Feb 11;6:20772. doi: 10.1038/srep20772.

Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in...

Cite
Engelhardt B, Frőhlich H, Kschischo M. Learning (from) the errors of a systems biology model. Sci Rep. 2016;6:20772doi: 10.1038/srep20772.
Engelhardt, B., Frőhlich, H., & Kschischo, M. (2016). Learning (from) the errors of a systems biology model. Scientific reports, 620772. https://doi.org/10.1038/srep20772
Engelhardt, Benjamin, et al. "Learning (from) the errors of a systems biology model." Scientific reports vol. 6 (2016): 20772. doi: https://doi.org/10.1038/srep20772
Engelhardt B, Frőhlich H, Kschischo M. Learning (from) the errors of a systems biology model. Sci Rep. 2016 Feb 11;6:20772. doi: 10.1038/srep20772. PMID: 26865316; PMCID: PMC4749970.
Copy Download .nbib Format: NLM
Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes.

PLoS computational biology

Mayourian J, Savizky RM, Sobie EA, Costa KD.
PMID: 27454812
PLoS Comput Biol. 2016 Jul 25;12(7):e1005014. doi: 10.1371/journal.pcbi.1005014. eCollection 2016 Jul.

Human mesenchymal stem cell (hMSC) delivery has demonstrated promise in preclinical and clinical trials for myocardial infarction therapy; however, broad acceptance is hindered by limited understanding of hMSC-human cardiomyocyte (hCM) interactions. To better understand the electrophysiological consequences of direct...

Cite
Mayourian J, Savizky RM, Sobie EA, et al. Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes. PLoS Comput Biol. 2016;12(7):e1005014doi: 10.1371/journal.pcbi.1005014.
Mayourian, J., Savizky, R. M., Sobie, E. A., & Costa, K. D. (2016). Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes. PLoS computational biology, 12(7), e1005014. https://doi.org/10.1371/journal.pcbi.1005014
Mayourian, Joshua, et al. "Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes." PLoS computational biology vol. 12,7 (2016): e1005014. doi: https://doi.org/10.1371/journal.pcbi.1005014
Mayourian J, Savizky RM, Sobie EA, Costa KD. Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes. PLoS Comput Biol. 2016 Jul 25;12(7):e1005014. doi: 10.1371/journal.pcbi.1005014. eCollection 2016 Jul. PMID: 27454812; PMCID: PMC4959759.
Copy Download .nbib Format: NLM
Life course models for upper aero-digestive tract cancer.

International dental journal

Gupta B, Lalloo R, Johnson NW.
PMID: 25939378
Int Dent J. 2015 Jun;65(3):111-9. doi: 10.1111/idj.12167. Epub 2015 May 01.

Upper aero-digestive tract (UADT) cancers are collectively cancers of various human body sites, such as the oral cavity, pharynx, oesophagus and larynx. Worldwide, they are the fourth most frequent cancer type and the fourth most common cause of mortality...

Cite
Gupta B, Lalloo R, Johnson NW. Life course models for upper aero-digestive tract cancer. Int Dent J. 2015;65(3):111-9doi: 10.1111/idj.12167.
Gupta, B., Lalloo, R., & Johnson, N. W. (2015). Life course models for upper aero-digestive tract cancer. International dental journal, 65(3), 111-9. https://doi.org/10.1111/idj.12167
Gupta, Bhawna, et al. "Life course models for upper aero-digestive tract cancer." International dental journal vol. 65,3 (2015): 111-9. doi: https://doi.org/10.1111/idj.12167
Gupta B, Lalloo R, Johnson NW. Life course models for upper aero-digestive tract cancer. Int Dent J. 2015 Jun;65(3):111-9. doi: 10.1111/idj.12167. Epub 2015 May 01. PMID: 25939378.
Copy Download .nbib Format: NLM
Predicting global community properties from uncertain estimates of interaction strengths.

Journal of the Royal Society, Interface

Barabás G, Allesina S.
PMID: 26246417
J R Soc Interface. 2015 Aug 06;12(109):20150218. doi: 10.1098/rsif.2015.0218.

The community matrix measures the direct effect of species on each other in an ecological community. It can be used to determine whether a system is stable (returns to equilibrium after small perturbations of the population abundances), reactive (perturbations...

Cite
Barabás G, Allesina S. Predicting global community properties from uncertain estimates of interaction strengths. J R Soc Interface. 2015;12(109):20150218doi: 10.1098/rsif.2015.0218.
Barabás, G., & Allesina, S. (2015). Predicting global community properties from uncertain estimates of interaction strengths. Journal of the Royal Society, Interface, 12(109), 20150218. https://doi.org/10.1098/rsif.2015.0218
Barabás, György, and Allesina, Stefano. "Predicting global community properties from uncertain estimates of interaction strengths." Journal of the Royal Society, Interface vol. 12,109 (2015): 20150218. doi: https://doi.org/10.1098/rsif.2015.0218
Barabás G, Allesina S. Predicting global community properties from uncertain estimates of interaction strengths. J R Soc Interface. 2015 Aug 06;12(109):20150218. doi: 10.1098/rsif.2015.0218. PMID: 26246417; PMCID: PMC4535399.
Copy Download .nbib Format: NLM
Understanding complex biogeographic responses to climate change.

Scientific reports

Seabra R, Wethey DS, Santos AM, Lima FP.
PMID: 26245256
Sci Rep. 2015 Aug 06;5:12930. doi: 10.1038/srep12930.

Predicting the extent and direction of species' range shifts is a major priority for scientists and resource managers. Seminal studies have fostered the notion that biological systems responding to climate change-impacted variables (e.g., temperature, precipitation) should exhibit poleward range...

Cite
Seabra R, Wethey DS, Santos AM, et al. Understanding complex biogeographic responses to climate change. Sci Rep. 2015;5:12930doi: 10.1038/srep12930.
Seabra, R., Wethey, D. S., Santos, A. M., & Lima, F. P. (2015). Understanding complex biogeographic responses to climate change. Scientific reports, 512930. https://doi.org/10.1038/srep12930
Seabra, Rui, et al. "Understanding complex biogeographic responses to climate change." Scientific reports vol. 5 (2015): 12930. doi: https://doi.org/10.1038/srep12930
Seabra R, Wethey DS, Santos AM, Lima FP. Understanding complex biogeographic responses to climate change. Sci Rep. 2015 Aug 06;5:12930. doi: 10.1038/srep12930. PMID: 26245256; PMCID: PMC4526865.
Copy Download .nbib Format: NLM
Estimating gene regulatory networks with pandaR.

Bioinformatics (Oxford, England)

Schlauch D, Paulson JN, Young A, Glass K, Quackenbush J.
PMID: 28334344
Bioinformatics. 2017 Jul 15;33(14):2232-2234. doi: 10.1093/bioinformatics/btx139.

CONTACT: [email protected] or [email protected] AND IMPLEMENTATION: PandaR is provided as a Bioconductor R Package and is available at bioconductor.org/packages/pandaR.

Cite
Schlauch D, Paulson JN, Young A, et al. Estimating gene regulatory networks with pandaR. Bioinformatics. 2017;33(14):2232-2234doi: 10.1093/bioinformatics/btx139.
Schlauch, D., Paulson, J. N., Young, A., Glass, K., & Quackenbush, J. (2017). Estimating gene regulatory networks with pandaR. Bioinformatics (Oxford, England), 33(14), 2232-2234. https://doi.org/10.1093/bioinformatics/btx139
Schlauch, Daniel, et al. "Estimating gene regulatory networks with pandaR." Bioinformatics (Oxford, England) vol. 33,14 (2017): 2232-2234. doi: https://doi.org/10.1093/bioinformatics/btx139
Schlauch D, Paulson JN, Young A, Glass K, Quackenbush J. Estimating gene regulatory networks with pandaR. Bioinformatics. 2017 Jul 15;33(14):2232-2234. doi: 10.1093/bioinformatics/btx139. PMID: 28334344; PMCID: PMC5870629.
Copy Download .nbib Format: NLM
Constraint-based stoichiometric modelling from single organisms to microbial communities.

Journal of the Royal Society, Interface

Gottstein W, Olivier BG, Bruggeman FJ, Teusink B.
PMID: 28334697
J R Soc Interface. 2016 Nov;13(124). doi: 10.1098/rsif.2016.0627.

Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and...

Cite
Gottstein W, Olivier BG, Bruggeman FJ, et al. Constraint-based stoichiometric modelling from single organisms to microbial communities. J R Soc Interface. 2016;13(124)doi: 10.1098/rsif.2016.0627.
Gottstein, W., Olivier, B. G., Bruggeman, F. J., & Teusink, B. (2016). Constraint-based stoichiometric modelling from single organisms to microbial communities. Journal of the Royal Society, Interface, 13(124), . https://doi.org/10.1098/rsif.2016.0627
Gottstein, Willi, et al. "Constraint-based stoichiometric modelling from single organisms to microbial communities." Journal of the Royal Society, Interface vol. 13,124 (2016). doi: https://doi.org/10.1098/rsif.2016.0627
Gottstein W, Olivier BG, Bruggeman FJ, Teusink B. Constraint-based stoichiometric modelling from single organisms to microbial communities. J R Soc Interface. 2016 Nov;13(124). doi: 10.1098/rsif.2016.0627. PMID: 28334697; PMCID: PMC5134014.
Copy Download .nbib Format: NLM
Conditions for duality between fluxes and concentrations in biochemical networks.

Journal of theoretical biology

Fleming RMT, Vlassis N, Thiele I, Saunders MA.
PMID: 27345817
J Theor Biol. 2016 Nov 21;409:1-10. doi: 10.1016/j.jtbi.2016.06.033. Epub 2016 Jun 23.

Mathematical and computational modelling of biochemical networks is often done in terms of either the concentrations of molecular species or the fluxes of biochemical reactions. When is mathematical modelling from either perspective equivalent to the other? Mathematical duality translates...

Cite
Fleming RMT, Vlassis N, Thiele I, et al. Conditions for duality between fluxes and concentrations in biochemical networks. J Theor Biol. 2016;409:1-10doi: 10.1016/j.jtbi.2016.06.033.
Fleming, R. M. T., Vlassis, N., Thiele, I., & Saunders, M. A. (2016). Conditions for duality between fluxes and concentrations in biochemical networks. Journal of theoretical biology, 4091-10. https://doi.org/10.1016/j.jtbi.2016.06.033
Fleming, Ronan M T, et al. "Conditions for duality between fluxes and concentrations in biochemical networks." Journal of theoretical biology vol. 409 (2016): 1-10. doi: https://doi.org/10.1016/j.jtbi.2016.06.033
Fleming RMT, Vlassis N, Thiele I, Saunders MA. Conditions for duality between fluxes and concentrations in biochemical networks. J Theor Biol. 2016 Nov 21;409:1-10. doi: 10.1016/j.jtbi.2016.06.033. Epub 2016 Jun 23. PMID: 27345817; PMCID: PMC5048525.
Copy Download .nbib Format: NLM
Disease Surveillance on Complex Social Networks.

PLoS computational biology

Herrera JL, Srinivasan R, Brownstein JS, Galvani AP, Meyers LA.
PMID: 27415615
PLoS Comput Biol. 2016 Jul 14;12(7):e1004928. doi: 10.1371/journal.pcbi.1004928. eCollection 2016 Jul.

As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs...

Cite
Herrera JL, Srinivasan R, Brownstein JS, et al. Disease Surveillance on Complex Social Networks. PLoS Comput Biol. 2016;12(7):e1004928doi: 10.1371/journal.pcbi.1004928.
Herrera, J. L., Srinivasan, R., Brownstein, J. S., Galvani, A. P., & Meyers, L. A. (2016). Disease Surveillance on Complex Social Networks. PLoS computational biology, 12(7), e1004928. https://doi.org/10.1371/journal.pcbi.1004928
Herrera, Jose L, et al. "Disease Surveillance on Complex Social Networks." PLoS computational biology vol. 12,7 (2016): e1004928. doi: https://doi.org/10.1371/journal.pcbi.1004928
Herrera JL, Srinivasan R, Brownstein JS, Galvani AP, Meyers LA. Disease Surveillance on Complex Social Networks. PLoS Comput Biol. 2016 Jul 14;12(7):e1004928. doi: 10.1371/journal.pcbi.1004928. eCollection 2016 Jul. PMID: 27415615; PMCID: PMC4944951.
Copy Download .nbib Format: NLM
Showing 49 to 60 of 1077 entries