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Items: 1 to 20 of 39

1.

Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach.

Casas B, Viola F, Cedersund G, Bolger AF, Karlsson M, Carlhäll CJ, Ebbers T.

Front Physiol. 2018 Oct 30;9:1515. doi: 10.3389/fphys.2018.01515. eCollection 2018.

PMID:
30425650
2.

Systems biology reveals uncoupling beyond UCP1 in human white fat-derived beige adipocytes.

Nyman E, Bartesaghi S, Melin Rydfalk R, Eng S, Pollard C, Gennemark P, Peng XR, Cedersund G.

NPJ Syst Biol Appl. 2017 Oct 3;3:29. doi: 10.1038/s41540-017-0027-y. eCollection 2017.

3.

Bridging the gap between measurements and modelling: a cardiovascular functional avatar.

Casas B, Lantz J, Viola F, Cedersund G, Bolger AF, Carlhäll CJ, Karlsson M, Ebbers T.

Sci Rep. 2017 Jul 24;7(1):6214. doi: 10.1038/s41598-017-06339-0.

4.

Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study.

Sten S, Lundengård K, Witt ST, Cedersund G, Elinder F, Engström M.

Neuroimage. 2017 Sep;158:219-231. doi: 10.1016/j.neuroimage.2017.07.002. Epub 2017 Jul 4.

PMID:
28687518
5.

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

Magnusson R, Mariotti GP, Köpsén M, Lövfors W, Gawel DR, Jörnsten R, Linde J, Nordling TEM, Nyman E, Schulze S, Nestor CE, Zhang H, Cedersund G, Benson M, Tjärnberg A, Gustafsson M.

PLoS Comput Biol. 2017 Jun 22;13(6):e1005608. doi: 10.1371/journal.pcbi.1005608. eCollection 2017 Jun.

6.

A systems biology analysis connects insulin receptor signaling with glucose transporter translocation in rat adipocytes.

Bergqvist N, Nyman E, Cedersund G, Stenkula KG.

J Biol Chem. 2017 Jul 7;292(27):11206-11217. doi: 10.1074/jbc.M117.787515. Epub 2017 May 11.

7.

Using a 3% Proton Density Fat Fraction as a Cut-Off Value Increases Sensitivity of Detection of Hepatic Steatosis, Based on Results From Histopathology Analysis.

Nasr P, Forsgren MF, Ignatova S, Dahlström N, Cedersund G, Leinhard OD, Norén B, Ekstedt M, Lundberg P, Kechagias S.

Gastroenterology. 2017 Jul;153(1):53-55.e7. doi: 10.1053/j.gastro.2017.03.005. Epub 2017 Mar 9.

PMID:
28286210
8.

Cross-talks via mTORC2 can explain enhanced activation in response to insulin in diabetic patients.

Magnusson R, Gustafsson M, Cedersund G, Strålfors P, Nyman E.

Biosci Rep. 2017 Jan 24;37(1). pii: BSR20160514. doi: 10.1042/BSR20160514. Print 2017 Feb 28.

9.

Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI.

Lundengård K, Cedersund G, Sten S, Leong F, Smedberg A, Elinder F, Engström M.

PLoS Comput Biol. 2016 Jun 16;12(6):e1004971. doi: 10.1371/journal.pcbi.1004971. eCollection 2016 Jun.

10.

Systems-wide Experimental and Modeling Analysis of Insulin Signaling through Forkhead Box Protein O1 (FOXO1) in Human Adipocytes, Normally and in Type 2 Diabetes.

Rajan MR, Nyman E, Kjølhede P, Cedersund G, Strålfors P.

J Biol Chem. 2016 Jul 22;291(30):15806-19. doi: 10.1074/jbc.M116.715763. Epub 2016 May 20.

11.

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes.

Nyman E, Rozendaal YJ, Helmlinger G, Hamrén B, Kjellsson MC, Strålfors P, van Riel NA, Gennemark P, Cedersund G.

Interface Focus. 2016 Apr 6;6(2):20150075. doi: 10.1098/rsfs.2015.0075. Review.

12.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.

Schleicher J, Conrad T, Gustafsson M, Cedersund G, Guthke R, Linde J.

Brief Funct Genomics. 2017 Mar 1;16(2):57-69. doi: 10.1093/bfgp/elv064. Review.

13.

Model-Based Quantification of the Systemic Interplay between Glucose and Fatty Acids in the Postprandial State.

Sips FL, Nyman E, Adiels M, Hilbers PA, Strålfors P, van Riel NA, Cedersund G.

PLoS One. 2015 Sep 10;10(9):e0135665. doi: 10.1371/journal.pone.0135665. eCollection 2015.

14.

Nonlinear mixed-effects modelling for single cell estimation: when, why, and how to use it.

Karlsson M, Janzén DL, Durrieu L, Colman-Lerner A, Kjellsson MC, Cedersund G.

BMC Syst Biol. 2015 Sep 4;9:52. doi: 10.1186/s12918-015-0203-x.

15.

Mathematical modeling improves EC50 estimations from classical dose-response curves.

Nyman E, Lindgren I, Lövfors W, Lundengård K, Cervin I, Sjöström TA, Altimiras J, Cedersund G.

FEBS J. 2015 Mar;282(5):951-62. doi: 10.1111/febs.13194. Epub 2015 Feb 6.

16.

Dominant negative inhibition data should be analyzed using mathematical modeling--re-interpreting data from insulin signaling.

Jullesson D, Johansson R, Rajan MR, Strålfors P, Cedersund G.

FEBS J. 2015 Feb;282(4):788-802. doi: 10.1111/febs.13182. Epub 2015 Jan 20.

17.

A single mechanism can explain network-wide insulin resistance in adipocytes from obese patients with type 2 diabetes.

Nyman E, Rajan MR, Fagerholm S, Brännmark C, Cedersund G, Strålfors P.

J Biol Chem. 2014 Nov 28;289(48):33215-30. doi: 10.1074/jbc.M114.608927. Epub 2014 Oct 15.

18.

Effects of IL-1β-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms.

Palmér R, Nyman E, Penney M, Marley A, Cedersund G, Agoram B.

CPT Pharmacometrics Syst Pharmacol. 2014 Jun 11;3:e118. doi: 10.1038/psp.2014.16.

19.

Physiologically realistic and validated mathematical liver model reveals [corrected] hepatobiliary transfer rates for Gd-EOB-DTPA using human DCE-MRI data.

Forsgren MF, Dahlqvist Leinhard O, Dahlström N, Cedersund G, Lundberg P.

PLoS One. 2014 Apr 18;9(4):e95700. doi: 10.1371/journal.pone.0095700. eCollection 2014. Erratum in: PLoS One. 2014;9(7):e104570.

20.

Combining test statistics and models in bootstrapped model rejection: it is a balancing act.

Johansson R, Strålfors P, Cedersund G.

BMC Syst Biol. 2014 Apr 17;8:46. doi: 10.1186/1752-0509-8-46.

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