Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 14 entries
Sorted by: Best Match Show Resources per page
The Maternal Gut Microbiome During Pregnancy.

MCN. The American journal of maternal child nursing

Edwards SM, Cunningham SA, Dunlop AL, Corwin EJ.
PMID: 28787280
MCN Am J Matern Child Nurs. 2017 Nov/Dec;42(6):310-317. doi: 10.1097/NMC.0000000000000372.

The gut microbiome is a critical component of an individual's metabolism and overall health. The prenatal period is marked by unique inflammatory and immune changes that alter maternal gut function and bacterial composition as the pregnancy advances. The composition...

Cite
Edwards SM, Cunningham SA, Dunlop AL, et al. The Maternal Gut Microbiome During Pregnancy. MCN Am J Matern Child Nurs. 2017;42(6):310-317doi: 10.1097/NMC.0000000000000372.
Edwards, S. M., Cunningham, S. A., Dunlop, A. L., & Corwin, E. J. (2017). The Maternal Gut Microbiome During Pregnancy. MCN. The American journal of maternal child nursing, 42(6), 310-317. https://doi.org/10.1097/NMC.0000000000000372
Edwards, Sara M, et al. "The Maternal Gut Microbiome During Pregnancy." MCN. The American journal of maternal child nursing vol. 42,6 (2017): 310-317. doi: https://doi.org/10.1097/NMC.0000000000000372
Edwards SM, Cunningham SA, Dunlop AL, Corwin EJ. The Maternal Gut Microbiome During Pregnancy. MCN Am J Matern Child Nurs. 2017 Nov/Dec;42(6):310-317. doi: 10.1097/NMC.0000000000000372. PMID: 28787280; PMCID: PMC5648614.
Copy Download .nbib Format: NLM
Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations.

Metabolic engineering

Hameri T, Fengos G, Ataman M, Miskovic L, Hatzimanikatis V.
PMID: 30455161
Metab Eng. 2019 Mar;52:29-41. doi: 10.1016/j.ymben.2018.10.005. Epub 2018 Oct 26.

Large-scale kinetic models are used for designing, predicting, and understanding the metabolic responses of living cells. Kinetic models are particularly attractive for the biosynthesis of target molecules in cells as they are typically better than other types of models...

Cite
Hameri T, Fengos G, Ataman M, et al. Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations. Metab Eng. 2018;52:29-41doi: 10.1016/j.ymben.2018.10.005.
Hameri, T., Fengos, G., Ataman, M., Miskovic, L., & Hatzimanikatis, V. (2019). Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations. Metabolic engineering, 5229-41. https://doi.org/10.1016/j.ymben.2018.10.005
Hameri, Tuure, et al. "Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations." Metabolic engineering vol. 52 (2019): 29-41. doi: https://doi.org/10.1016/j.ymben.2018.10.005
Hameri T, Fengos G, Ataman M, Miskovic L, Hatzimanikatis V. Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations. Metab Eng. 2019 Mar;52:29-41. doi: 10.1016/j.ymben.2018.10.005. Epub 2018 Oct 26. PMID: 30455161.
Copy Download .nbib Format: NLM
Four years, 400 articles, IF 5.4, and fast-track into PubMed.

Molecular metabolism

[No authors listed]
PMID: 28123929
Mol Metab. 2017 Jan 07;6(1):1. doi: 10.1016/j.molmet.2016.12.003. eCollection 2017 Jan.

No abstract available.

Cite
Four years, 400 articles, IF 5.4, and fast-track into PubMed. Mol Metab. 2017;6(1):1doi: 10.1016/j.molmet.2016.12.003.
(2017). Four years, 400 articles, IF 5.4, and fast-track into PubMed. Molecular metabolism, 6(1), 1. https://doi.org/10.1016/j.molmet.2016.12.003
"Four years, 400 articles, IF 5.4, and fast-track into PubMed." Molecular metabolism vol. 6,1 (2017): 1. doi: https://doi.org/10.1016/j.molmet.2016.12.003
Four years, 400 articles, IF 5.4, and fast-track into PubMed. Mol Metab. 2017 Jan 07;6(1):1. doi: 10.1016/j.molmet.2016.12.003. eCollection 2017 Jan. PMID: 28123929; PMCID: PMC5220534.
Copy Download .nbib Format: NLM
Metabolic profiling: pathways in discovery.

Drug discovery today

Goodacre R.
PMID: 15003243
Drug Discov Today. 2004 Mar 15;9(6):260-1. doi: 10.1016/S1359-6446(04)03027-2.

No abstract available.

Cite
Goodacre R. Metabolic profiling: pathways in discovery. Drug Discov Today. 2004;9(6):260-1doi: 10.1016/S1359-6446(04)03027-2.
Goodacre, R. (2004). Metabolic profiling: pathways in discovery. Drug discovery today, 9(6), 260-1. https://doi.org/10.1016/S1359-6446(04)03027-2
Goodacre, Royston. "Metabolic profiling: pathways in discovery." Drug discovery today vol. 9,6 (2004): 260-1. doi: https://doi.org/10.1016/S1359-6446(04)03027-2
Goodacre R. Metabolic profiling: pathways in discovery. Drug Discov Today. 2004 Mar 15;9(6):260-1. doi: 10.1016/S1359-6446(04)03027-2. PMID: 15003243.
Copy Download .nbib Format: NLM
Emergent biosynthetic capacity in simple microbial communities.

PLoS computational biology

Chiu HC, Levy R, Borenstein E.
PMID: 24992662
PLoS Comput Biol. 2014 Jul 03;10(7):e1003695. doi: 10.1371/journal.pcbi.1003695. eCollection 2014 Jul.

Microbes have an astonishing capacity to transform their environments. Yet, the metabolic capacity of a single species is limited and the vast majority of microorganisms form complex communities and join forces to exhibit capabilities far exceeding those achieved by...

Cite
Chiu HC, Levy R, Borenstein E. Emergent biosynthetic capacity in simple microbial communities. PLoS Comput Biol. 2014;10(7):e1003695doi: 10.1371/journal.pcbi.1003695.
Chiu, H. C., Levy, R., & Borenstein, E. (2014). Emergent biosynthetic capacity in simple microbial communities. PLoS computational biology, 10(7), e1003695. https://doi.org/10.1371/journal.pcbi.1003695
Chiu, Hsuan-Chao, et al. "Emergent biosynthetic capacity in simple microbial communities." PLoS computational biology vol. 10,7 (2014): e1003695. doi: https://doi.org/10.1371/journal.pcbi.1003695
Chiu HC, Levy R, Borenstein E. Emergent biosynthetic capacity in simple microbial communities. PLoS Comput Biol. 2014 Jul 03;10(7):e1003695. doi: 10.1371/journal.pcbi.1003695. eCollection 2014 Jul. PMID: 24992662; PMCID: PMC4084645.
Copy Download .nbib Format: NLM
Metabolism and cancer in La Jolla.

Cancer research

Shaw RJ, Evans RM, Simon MC.
PMID: 20442287
Cancer Res. 2010 May 15;70(10):3864-9. doi: 10.1158/0008-5472.CAN-09-4529. Epub 2010 May 04.

No abstract available.

Cite
Shaw RJ, Evans RM, Simon MC. Metabolism and cancer in La Jolla. Cancer Res. 2010;70(10):3864-9doi: 10.1158/0008-5472.CAN-09-4529.
Shaw, R. J., Evans, R. M., & Simon, M. C. (2010). Metabolism and cancer in La Jolla. Cancer research, 70(10), 3864-9. https://doi.org/10.1158/0008-5472.CAN-09-4529
Shaw, Reuben J, et al. "Metabolism and cancer in La Jolla." Cancer research vol. 70,10 (2010): 3864-9. doi: https://doi.org/10.1158/0008-5472.CAN-09-4529
Shaw RJ, Evans RM, Simon MC. Metabolism and cancer in La Jolla. Cancer Res. 2010 May 15;70(10):3864-9. doi: 10.1158/0008-5472.CAN-09-4529. Epub 2010 May 04. PMID: 20442287; PMCID: PMC2873170.
Copy Download .nbib Format: NLM
Max Rubner (1854-1932).

Obesity reviews : an official journal of the International Association for the Study of Obesity

Rössner S.
PMID: 23590696
Obes Rev. 2013 May;14(5):432-3. doi: 10.1111/obr.12023.

No abstract available.

Cite
Rössner S. Max Rubner (1854-1932). Obes Rev. 2013;14(5):432-3doi: 10.1111/obr.12023.
Rössner, S. (2013). Max Rubner (1854-1932). Obesity reviews : an official journal of the International Association for the Study of Obesity, 14(5), 432-3. https://doi.org/10.1111/obr.12023
Rössner, Stephan. "Max Rubner (1854-1932)." Obesity reviews : an official journal of the International Association for the Study of Obesity vol. 14,5 (2013): 432-3. doi: https://doi.org/10.1111/obr.12023
Rössner S. Max Rubner (1854-1932). Obes Rev. 2013 May;14(5):432-3. doi: 10.1111/obr.12023. PMID: 23590696.
Copy Download .nbib Format: NLM
2020: a year of loss and delays.

Nature metabolism

[No authors listed]
PMID: 32943785
Nat Metab. 2020 Sep;2(9):795. doi: 10.1038/s42255-020-00286-3.

No abstract available.

Cite
2020: a year of loss and delays. Nat Metab. 2020;2(9):795doi: 10.1038/s42255-020-00286-3.
(2020). 2020: a year of loss and delays. Nature metabolism, 2(9), 795. https://doi.org/10.1038/s42255-020-00286-3
"2020: a year of loss and delays." Nature metabolism vol. 2,9 (2020): 795. doi: https://doi.org/10.1038/s42255-020-00286-3
2020: a year of loss and delays. Nat Metab. 2020 Sep;2(9):795. doi: 10.1038/s42255-020-00286-3. PMID: 32943785.
Copy Download .nbib Format: NLM
Metabolism: from bench to bedside.

Nature medicine

Firestein GS.
PMID: 20376049
Nat Med. 2010 Apr;16(4):387. doi: 10.1038/nm0410-387.

No abstract available.

Cite
Firestein GS. Metabolism: from bench to bedside. Nat Med. 2010;16(4):387doi: 10.1038/nm0410-387.
Firestein, G. S. (2010). Metabolism: from bench to bedside. Nature medicine, 16(4), 387. https://doi.org/10.1038/nm0410-387
Firestein, Gary S. "Metabolism: from bench to bedside." Nature medicine vol. 16,4 (2010): 387. doi: https://doi.org/10.1038/nm0410-387
Firestein GS. Metabolism: from bench to bedside. Nat Med. 2010 Apr;16(4):387. doi: 10.1038/nm0410-387. PMID: 20376049.
Copy Download .nbib Format: NLM
A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.

Theoretical biology & medical modelling

Kitayama T, Kinoshita A, Sugimoto M, Nakayama Y, Tomita M.
PMID: 16846504
Theor Biol Med Model. 2006 Jul 17;3:24. doi: 10.1186/1742-4682-3-24.

BACKGROUND: In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time...

Cite
Kitayama T, Kinoshita A, Sugimoto M, et al. A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles. Theor Biol Med Model. 2006;3:24doi: 10.1186/1742-4682-3-24.
Kitayama, T., Kinoshita, A., Sugimoto, M., Nakayama, Y., & Tomita, M. (2006). A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles. Theoretical biology & medical modelling, 324. https://doi.org/10.1186/1742-4682-3-24
Kitayama, Tomoya, et al. "A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles." Theoretical biology & medical modelling vol. 3 (2006): 24. doi: https://doi.org/10.1186/1742-4682-3-24
Kitayama T, Kinoshita A, Sugimoto M, Nakayama Y, Tomita M. A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles. Theor Biol Med Model. 2006 Jul 17;3:24. doi: 10.1186/1742-4682-3-24. PMID: 16846504; PMCID: PMC1550393.
Copy Download .nbib Format: NLM
[Metabolism and health: yesterday--today-tomorrow].

Pharmazie in unserer Zeit

Klumpp S, Selke D.
PMID: 9304116
Pharm Unserer Zeit. 1997 May;26(3):123-6. doi: 10.1002/pauz.19970260305.

No abstract available.

Cite
Klumpp S, Selke D. Stoffwechsel und Nahrung gestern-heute-morgen. [Metabolism and health: yesterday--today-tomorrow]. Pharm Unserer Zeit. 1997;26(3):123-6doi: 10.1002/pauz.19970260305.
Klumpp, S., & Selke, D. (1997). Stoffwechsel und Nahrung gestern-heute-morgen. [Metabolism and health: yesterday--today-tomorrow]. Pharmazie in unserer Zeit, 26(3), 123-6. https://doi.org/10.1002/pauz.19970260305
Klumpp, S, and Selke, D. "Stoffwechsel und Nahrung gestern-heute-morgen." [Metabolism and health: yesterday--today-tomorrow]. Pharmazie in unserer Zeit vol. 26,3 (1997): 123-6. doi: https://doi.org/10.1002/pauz.19970260305
Klumpp S, Selke D. Stoffwechsel und Nahrung gestern-heute-morgen. [Metabolism and health: yesterday--today-tomorrow]. Pharm Unserer Zeit. 1997 May;26(3):123-6. doi: 10.1002/pauz.19970260305. German. PMID: 9304116.
Copy Download .nbib Format: NLM
Communication at a Distance.

Developmental cell

[No authors listed]
PMID: 32693051
Dev Cell. 2020 Jul 20;54(2):133. doi: 10.1016/j.devcel.2020.06.040.

No abstract available.

Cite
Communication at a Distance. Dev Cell. 2020;54(2):133doi: 10.1016/j.devcel.2020.06.040.
(2020). Communication at a Distance. Developmental cell, 54(2), 133. https://doi.org/10.1016/j.devcel.2020.06.040
"Communication at a Distance." Developmental cell vol. 54,2 (2020): 133. doi: https://doi.org/10.1016/j.devcel.2020.06.040
Communication at a Distance. Dev Cell. 2020 Jul 20;54(2):133. doi: 10.1016/j.devcel.2020.06.040. PMID: 32693051; PMCID: PMC7370899.
Copy Download .nbib Format: NLM
Showing 1 to 12 of 14 entries