workshop on 'The interplay of fat and carbohydrate metabolism with application in Metabolic Syndrome and Type 2 Diabetes', December 12 and 13, 2013, Eindhoven University of Technology
Systems biology & Approaches of genomics and proteomicssonam786
This presentation provides the basic understanding of varous genomics and proteomics techniques.Systems biology studies life as a system .It includes the study of living system using various omic technologies .
It encloses a brief description of flux balance analysis tools, flux measuring software, methods, advantages and comparable applications to the other software's and analysis techniques and discussion so on steady - constraint based analysis modelling, reconstruction of metabolic pathways and different constraints. etc.
Metabolic engineering is a branch of bioengineering where the use of genetic engineering and recombinant technology to modify the metabolism of an organism.
Systems biology & Approaches of genomics and proteomicssonam786
This presentation provides the basic understanding of varous genomics and proteomics techniques.Systems biology studies life as a system .It includes the study of living system using various omic technologies .
It encloses a brief description of flux balance analysis tools, flux measuring software, methods, advantages and comparable applications to the other software's and analysis techniques and discussion so on steady - constraint based analysis modelling, reconstruction of metabolic pathways and different constraints. etc.
Metabolic engineering is a branch of bioengineering where the use of genetic engineering and recombinant technology to modify the metabolism of an organism.
Proteomics studies play an increasing role in the field of biology. The use of mass spectrometry (MS) in combination with a range of separation methods is the main principal methodology for proteomics. The two principal approaches to identifying and characterizing proteins using MS are the “bottom-up”, which analyze peptides by proteolytic digestion, and “top-down”, which analyze intact proteins.
Functional proteomics, methods and toolsKAUSHAL SAHU
INTRODUCTION
HISTORY
DEFINITION
PROTEOMICS
FUNCTIONAL PROTEOMICS
PROTEOMICS SOFTWARE
PROTEOMICS ANALYSIS
TOOLS FOR PROTEOM ANALYSIS
DIFFERENTS METHODS FOR STUDY OF FUNCTIONAL PROTEOMICS
APLLICATIONS
LIMITATIONS
CONCLUSION
INTRODUCTION
A PERFECT THERAPEUTIC DRUG
DRUG DISCOVERY- HISTORY
MODERN DRUG DISCOVERY
BIOINFORATICS IN DRUG DISCOVERY
DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS
BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY
ECONOMICS OF DRUG DISCOVERY
CONCLUSION
REFERENCES
Automated sequencing of genomes require automated gene assignment
Includes detection of open reading frames (ORFs)
Identification of the introns and exons
Gene prediction a very difficult problem in pattern recognition
Coding regions generally do not have conserved sequences
Much progress made with prokaryotic gene prediction
Eukaryotic genes more difficult to predict correctly
Ab Initio Protein Structure Prediction is a method to determine the tertiary structure of protein in the absence of experimentally solved structure of a similar/homologous protein. This method builds protein structure guided by energy function.
I had prepared this presentation for an internal project during my masters degree course.
After sequencing of the genome has been done, the first thing that comes to mind is "Where are the genes?". Genome annotation is the process of attaching information to the biological sequences. It is an active area of research and it would help scientists a lot to undergo with their wet lab projects once they know the coding parts of a genome.
description of functional genomics and structural genomics and the techniques involved in it and also decribing the models of forward genetics and techniques involved in it and reverse genetics and techniques involved in it
Proteomics studies play an increasing role in the field of biology. The use of mass spectrometry (MS) in combination with a range of separation methods is the main principal methodology for proteomics. The two principal approaches to identifying and characterizing proteins using MS are the “bottom-up”, which analyze peptides by proteolytic digestion, and “top-down”, which analyze intact proteins.
Functional proteomics, methods and toolsKAUSHAL SAHU
INTRODUCTION
HISTORY
DEFINITION
PROTEOMICS
FUNCTIONAL PROTEOMICS
PROTEOMICS SOFTWARE
PROTEOMICS ANALYSIS
TOOLS FOR PROTEOM ANALYSIS
DIFFERENTS METHODS FOR STUDY OF FUNCTIONAL PROTEOMICS
APLLICATIONS
LIMITATIONS
CONCLUSION
INTRODUCTION
A PERFECT THERAPEUTIC DRUG
DRUG DISCOVERY- HISTORY
MODERN DRUG DISCOVERY
BIOINFORATICS IN DRUG DISCOVERY
DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS
BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY
ECONOMICS OF DRUG DISCOVERY
CONCLUSION
REFERENCES
Automated sequencing of genomes require automated gene assignment
Includes detection of open reading frames (ORFs)
Identification of the introns and exons
Gene prediction a very difficult problem in pattern recognition
Coding regions generally do not have conserved sequences
Much progress made with prokaryotic gene prediction
Eukaryotic genes more difficult to predict correctly
Ab Initio Protein Structure Prediction is a method to determine the tertiary structure of protein in the absence of experimentally solved structure of a similar/homologous protein. This method builds protein structure guided by energy function.
I had prepared this presentation for an internal project during my masters degree course.
After sequencing of the genome has been done, the first thing that comes to mind is "Where are the genes?". Genome annotation is the process of attaching information to the biological sequences. It is an active area of research and it would help scientists a lot to undergo with their wet lab projects once they know the coding parts of a genome.
description of functional genomics and structural genomics and the techniques involved in it and also decribing the models of forward genetics and techniques involved in it and reverse genetics and techniques involved in it
Systems medicine of metabolic syndrome and its comorbiditiesNatal van Riel
Due to an aging population and the obesity epidemic, an increasing number of people suffer from the so-called Metabolic Syndrome (MetSyn). Those people have a combination of related disease phenotypes, such as high cholesterol, disturbed sugar metabolism and insulin insensitivity. Moreover, they are at a high risk to develop type 2 diabetes, fatty liver and cardiovascular diseases. We use systems biology to understand how the processes involved in metabolism of cholesterol, lipids and sugars become imbalanced. As an example, a study on the effect of Liver X receptor (LXR) agonists is reported.
Systems biology (systems medicine) research also triggers innovation in methods and technology for modelling. The application of a novel computational modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT) will be discussed. ADAPT is applied to describe the development and progression of MetSyn over a longer period of time. In combination with model-based experimental validation we study the physiological origin of hepatic steatosis induced by liver X receptor activation.
Molecular modelling for in silico drug discoveryLee Larcombe
A slide set based on the small molecule section of "Introduction to in silico drug discovery" with more detail on molecular modelling and simulation aspects. Including a bit more on protein structure prediction
QSAR Studies of the Inhibitory Activity of a Series of Substituted Indole and...inventionjournals
HF method, with the basis set 6-31G (d) was employed to calculate quantum some chemical descriptors of 37 substituted Indole. The best descriptors were selected to establish the quantitative structure activity relationship (QSAR) of the inhibitory activity against isoprenylcysteine carboxyl methyltransferase (Icmt), by principal components analysis (PCA), to a multiple regression analysis (MLR), to a nonlinear regression (RNLM) and to an artificial neural network (ANN). We accordingly propose a quantitative model and we interpret the activity of the compounds relying on the multivariate statistical analysis. This study shows that the MLR and have served to predict activity, but when compared with the results given by the ANN model. We concluded that the predictions achieved by this latter is more effective and much better than other models. The statistical results indicate that the model is statistically significant and shows very good stability towards data variation in the validation method. The contribution of each descriptor to the structure-activity relationship is evaluated.
Project report: Investigating the effect of cellular objectives on genome-sca...Jarle Pahr
Report from a half-semester master-level project carried out at the department of biotechnology, Norwegian University of Science and Technology. Describes a MATLAB-based framework for comparing experimental metabolic flux data with model predictions and evaluating objective functions.
Presentation made at PepTalk 2011 in San Diego on Jan. 13, 2011. The emphasis is on computational methods to explore global and local structure similarities in determining the possible promiscuity of drugs to bind to multiple protein receptors.
EXPERIMENTAL IMPLEMENTATION OF EMBARRASINGLY PARALLEL PROCESS IN ANALYSIS OF ...ijesajournal
This paper explains the development of a embedded based parallel system to measure glucose concentration of the blood samples. The developed instrument works on the principle of absorbance transmittance photometry using ATmega32 microcontrollers. In order to handle more blood samples and reduce the response time of glucose analyzing process in large number of blood samples, the embarrassing parallel measurement operation is implemented. The proposed system architecture and the co-design of hardware and software are discussed in detail. The system is evaluated using the
parameters of Speedup Factor, Efficiency and Throughput are studied. The result shows that system attained the linear speedup in measurement of blood samples.
Similar to Genome-Scale Metabolic Models and Systems Medicine of Metabolic Syndrome (20)
Quantification of variability and uncertainty in systems medicine modelsNatal van Riel
BioSB2016 Conference
Abstract: Computational modelling in systems biology addresses biological processes at different levels and scales. The quantification of model parameters from experimental data is a complicated task. To develop accurate, predictive models it is necessary to analyze how variance in data propagates into parameter estimates and, more importantly, model predictions. The network structure of the biological systems imposes strong constraints on possible solutions of a model. Amounts of data, available at molecular and physiological level, continue to increase. Often, model results are only partly in agreement with data, despite that model parameters are fitted. In contrast to existing belief that calibration of systems biology models to experimental data is prone to overfitting, we argue that dynamical models, despite their size and complexity, are not flexible enough to correctly describe all data.
Approaches are explored to introduce more degrees of freedom in models, but simultaneously enforcing sparsity if extra flexibility is not required. Estimation tools for dynamical systems are complemented with ‘regularization’ methods to reduce the error (bias) in models without escalating uncertainties (variance). This paradigm shift will be illustrated in two examples: 1) modelling of longitudinal data in a cohort of Type 2 Diabetics using different medication, and 2) the application in preclinical research studying the effect of liver X receptor activation on HDL metabolism and liver steatosis.
Roche Quantitative Systems Pharmacology methodology workshop
February 4th-5th, 2016, Basel, Switzerland
Bringing multi-level systems pharmacology models to life
Natal van Riel
Abstract
Computational modelling in Systems Medicine and Systems Pharmacology addresses biological processes at different levels and scales. The quantification of model parameters from experimental data is a complicated task. It will be addressed how variance in data propagates into parameter estimates and, more importantly, model predictions. The Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT) approach is discussed as method to model dynamics at multiple time-scales. Two examples will be provided: 1) modelling of longitudinal data in a cohort of Type 2 Diabetics using different medication, and 2) the application in preclinical research studying the effect of liver X receptor activation on HDL metabolism and liver steatosis.
MouseAGE Kickoff conference
Braga, Portugal
23 Mar 2015 to 25 Mar 2015
COST Action MouseAGE: Preclinical testing of interventions in mouse models of age and age-related diseases
http://www.cost.eu/COST_Actions/bmbs/Actions/BM1402
Disseminating the FP7 Systems Medicine of Metabolic Syndrome project RESOLVE (http://www.resolve-diabetes.org)
ADAPT: Analysis of Dynamic Adaptations in Parameter Trajectories Natal van Riel
Part of the Training Course: Data Integration in the Life Sciences.
from 2 Feb 2015 through 6 Feb 2015, Lorentz Center, Leiden
Organized by ERA-Net program for Systems Biology Applications (ERASysApp, https://www.erasysapp.eu/) and the Dutch systems biology and bioinformatics community (BioSB, http://biosb.nl).
http://www.lorentzcenter.nl/lc/web/2015/684/description.php3?wsid=684&venue=Snellius
The Eindhoven Diabetes Education Simulator (e-DES) - incorporating different ...Natal van Riel
Background: Diabetes education is mainly based on one-on-one patient-health care provider contact. This is costly, time-consuming and gives the patient no room for practice. We want to address these issues by creating the Eindhoven Diabetes Education Simulator, which uses a physiology-based mathematical model to predict glucose and insulin concentrations for patients with diabetes type 1 and 2 over a 2-4 hour time period after intake of food and/or insulin. In our current model food is entered in the form of carbohydrate content. The goal of this study was to incorporate different food products and composite meals for healthy persons, since different food types will elicit different glucose responses.
Methods: A literature search was performed for datasets of different food products using (combinations of) the following search terms: healthy, mixed meal, glucose, insulin, glycemic response, glycemic index, and looking for cross-references. We included any dataset for which glucose ánd insulin concentrations were measured on at least 5 time points after food ingestion in healthy subjects. Healthy was defined as normal glucose tolerant, normal insulin sensitive, normotensive, normal HbA1c, non-obese (BMI< 30 kg/m2), no family history of diabetes, not pregnant, and free of apparent diseases and medication. Our model was fitted to the different datasets using a non-linear least squares algorithm.
Results: We have fitted our model to 57 separate datasets (from 18 publications including 220 subjects, references available on request). For 35 of these datasets we obtained a model fit that described the dataset well, of which five are shown in Figure 1. In the cases that we could not obtain a good fit, there usually were a limited number of data points available.
Conclusion: The Eindhoven Diabetes Education Simulator is able to simulate postprandial glucose and insulin concentrations for healthy persons for 35 different food products and composite meals.
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
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These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Acute scrotum is a general term referring to an emergency condition affecting the contents or the wall of the scrotum.
There are a number of conditions that present acutely, predominantly with pain and/or swelling
A careful and detailed history and examination, and in some cases, investigations allow differentiation between these diagnoses. A prompt diagnosis is essential as the patient may require urgent surgical intervention
Testicular torsion refers to twisting of the spermatic cord, causing ischaemia of the testicle.
Testicular torsion results from inadequate fixation of the testis to the tunica vaginalis producing ischemia from reduced arterial inflow and venous outflow obstruction.
The prevalence of testicular torsion in adult patients hospitalized with acute scrotal pain is approximately 25 to 50 percent
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
Genome-Scale Metabolic Models and Systems Medicine of Metabolic Syndrome
1. Metabolic Syndrome workshop
Dec. 13, 2013
Eindhoven University of Technology, Eindhoven
Natal van Riel
Dept. of Biomedical Engineering, TU/e, n.a.w.v.riel@tue.nl
Systems Biology and Metabolic Diseases
2. Can we link understanding of metabolism and
biochemistry (incl. modeling)
to the multi-omics data that are collected in
in research projects
and in the clinic of the (near) future
and tendencies towards stratified
and personalized health and healthcare
/ biomedical engineering
16-12-2013 PAGE 2
3. Is the time right for application of GSMM‟s
…for a Systems Medicine approach of Metabolic Syndrome?
2007 Recon1
(Duarte 2007 PNAS 104(6): 1777)
2010 Hepatonet
(Gille 2010 Mol Syst Biol 6:411)
2013 Recon2
(Thiele et al. 2013, Nat Biotech.)
/ biomedical engineering
12/16/2013 PAGE 3
4. Recon 2
• Genome-Scale Metabolic Model
• Total number of reactions 7,440
• Total number of metabolites 5,063
• Number of unique metabolites 2,626
http://humanmetabolism.org/
/ biomedical engineering
16-12-2013 PAGE 4
5. Genome-scale metabolic reconstructions
Advantages:
• Especially good coverage of small, monomeric molecules and
central metabolism
• Comprehensive network topology (wiring)
Limitations:
• Manual curration needed of many pathways outside central
metabolism
• Weak in polymeric metabolites with large heterogeneity, e.g.,
lipids, lipoproteins
/ biomedical engineering
12/16/2013 PAGE 5
6. Applications of the global human metabolic
network
“Genome-scale metabolic network reconstructions provide a
platform to interpret omics data in a biochemically meaningful
manner.”
• Four classes of application:
1. Integration of „omics‟ data for tissue and cell specific
network reconstruction,
2. Mapping homologous genes for global mammalian network
reconstruction,
3. Contextualization of „omics‟ data from pathological and
drug-treated states,
4. Simulation of pathological and drug-treated states
/ biomedical engineering
16-12-2013 PAGE 6
7. Example:
a metabolic perspective on ADHD, autism
• Neurotransmission is disrupted in most psychiatric disorders
• Serotonergic system malfunctioning
• An underlying metabolic cause
Yap,et al 2010, J Proteome Res 9(6): 2996
/ biomedical engineering
16-12-2013 PAGE 7
8. Metabolomics of 24 hour urine
• Metabolomics
(N=362)
• Analysis and
interpretation with
network model
• Recon2, curated for
tryptophan metabolism
Dermois et al
/ biomedical engineering
12/16/2013 PAGE 8
9. HUMETICS HUman METabolic diagnostICS
Network-based analysis
APeT in collaboration with TU/e
Dermois, van den Eijnde et al
/ biomedical engineering
16-12-2013 PAGE 9
13. COnstraints Based Reconstruction and
Analysis (COBRA) methods
• So far, just the topology
• What about fluxes
• Flux Balance Analysis (FBA)
• Flux Variability Analysis (FVA)
• …
/ biomedical engineering
16-12-2013 PAGE 13
14. Network stoichiometry and Stoichiometric
Matrix
• A hypothetical network
• Stoichiometry matrix
• Stoichiometric model
d s (t )
N v ( s ( t ))
dt
with the species concentrations collated in a vector s
and the reaction rates in a vector v [ v1 , ..., v 5 ]T
/ biomedical engineering
16-12-2013 PAGE 14
[ s1 , ..., s 4 ]
T
15. Steady-state („homeostasis‟)
d s (t )
N v ( s ( t )) ˆ 0
dt
Nv
0
metabolite balancing equation
• Set of differential equations set of algebraic equations with
the rates in v unknown
1
1
1
0
0
1
1
0
1
1
0
0
0
0
0
0
0
0
1
1
v1
v2
v3
v4
v5
0
0
0
0
• Here 4 equations (4 species) and 5 unknowns
• an under-determined set of equations
• not a single solution
/ biomedical engineering
16-12-2013 PAGE 15
16. Metabolic Balancing Analysis
• Mass balances (Differential Equations)
• Steady-state (concentrations constant over time), (N v = 0)
• A metabolic fingerprint / snapshot
v0
Flux space
v1
v1
System of algebraic equations
v2
v0
v2
An underdetermined system
v1
v2
v1
v0
v2
v3
v3
v1
• Measurements to constrain the underdetermined system
• Isotopic tracers, e.g. 13C
• Solve / simulate with Flux Balance Analysis
/ biomedical engineering
16-12-2013 PAGE 16
17. Analyzing pathway diagrams
Two equivalent routes for
converting an input substrate into
an output metabolite
If we know/assume that the system
aims for minimization of total
(number of) intracellular fluxes
(efficiency), both routes are not
equivalent
If the objective is to maximize ATP
yield then also only one route will
be utilized
• Can be linked to an objective function to be minimized or
maximized in FBA
/ biomedical engineering
16-12-2013 PAGE 17
18. The conceptual basis of Flux Balance Analysis
With no constraints, the flux
distribution of a biological
network may lie at any point in
a solution space
Through optimization of an objective
function, FBA can identify a single
optimal flux distribution that lies on the
edge of the allowable solution space
N
mass balance constraints imposed by the stoichiometric matrix N + capacity
constraints imposed by the lower and upper bounds (ai and bi) are applied to a
network an allowable solution space
The network may acquire any flux distribution within this space, but points
outside this space are denied by the constraints
Orth et al. Nat Biotechnol. 2010; 28(3): 245-248
/ biomedical engineering
16-12-2013 PAGE 18
19. A multi-tissue type genome-scale metabolic
network
• Implications for blood-based metabolic biomarkers
Bordbar, et al., I. (2011) BMC Syst. Biol., 5, 180
/ biomedical engineering
16-12-2013 PAGE 19
20. Systems medicine and metabolic modelling
Mardinoglu & Nielsen. J Intern Med 2012; 271:142–154
/ biomedical engineering
16-12-2013 PAGE 20
21. Systems medicine and metabolic modelling
/ biomedical engineering
16-12-2013 PAGE 21