*"&'((ITP),+#$)&' !%Name-Sohiya Yotsukura
Title-Ph.D. candidate, 1st year
Institute: Bioinformatics Center (Mamitsuka Laboratory), Kyoto University Institute for
Chemical research; Kyoto, Uji, Gokasho 611-0011, Japan
Partner institute: Humboldt University, Institute of Biology, Department of TheoreticalPhysics (Edda Klipp Laboratory), Invalidenstraße 42, D-10115 Berlin, Germany
Duration: October 2013- December 2013
Report:During my stay at Humboldt University, I was able to interact with all the team members ofProfessor Edda Klipp’s laboratory understanding the current team’s focus within cellmodeling. I attended the frequent group meetings and presentations, as well as the occasionalseminar which provided an overview of the methods and issues that are currently dealt within the yeast cell modeling. The question that was mainly asked was “How does the yeast cell
respond to the stress conditions?” The yeast is a well-established model organism, and its
basic functions in yeast are highly similar to those of higher eukaryotes. An integrative
project was held to combine the Biosynthetic pathways, their regulations, the cell cycle, celldivision, transcription regulations and transcriptional activation, signal transduction
pathways, stress responses, nuclear-mitochondrial interactions (nuclear transport) andchromatin regulatory mechanisms to properly model the life cycle of the yeast cell in normal
and stress conditions. Even with this simplistic model, combining the various functions tomodel the regulatory and predictive functions is an extreme task. This made me even further
understand the complexity of nature and emphasized the need for research andunderstanding.
Till date, I have not worked much with yeast, but the methods that were intrigued me.
Hoping to learn more about the methodology and the tools used, I joined the workshop“Modellierung Biologischer Systeme” (19 November – 29 November 2013) to eventuallycontribute to the cross-fertilization between the research in machine learning methods andtheir applications to systems biology. The workshop covered the importance of SBML, thecurrent databases and resources, and a MATLAB and a Copasi tutorial. The intensive
workshop gave an overview of the tools need to develop a SBML model through theformulations of the biochemical reactions quantified through experiments.
The topic that chose was the mathematical model of the folate metabolism (Reed et al., 2004).
Using the biochemical reactions, complemented with the ODEs, I was able to create a basicmodel that simulated the folate metabolism system in eukaryotes. Copasi was used tooptimize the parameters needed to analyze the dynamic behavior and the steady-state
properties. Furthermore, a sensitivity analysis was performed to determine the values of themodel variables, which included both the local and the global sensitivity analysis of my model.
Optimization was performed using both Copasi and Matlab to numerically determine theproperties of the complex folate metabolism model. Finally, parameter estimation wasperformed with the published experimental data to calibrate the represented real biologicalsystem accurately, including the analysis of enzyme kinetic experiments, and in vivo timecourses of the published experiments. Using
the Copasi capabilities, the experimental ODE
model was represented stochastically andintegrated with the CellDesigner to create anetwork of the FOCM (folate-mediated one
carbon metabolism) reaction scheme. The
generated model was rather similar to thepublished finding with one exception.
Mymodel was not able to generate any flux in theMTD(5,10-methylenetetrahydrofolatedehydrogenase) enzyme (Table 1).
Thiseffected the concentrations of some substrates
and the fluxes of other integrative enzymes
within the FOCM reaction scheme (Diagram 1-a& 1-b). Ultimately, I was not able to reproduce
the exact published results, but established afirm understanding of how the current tools,

*"&'((ITP),+#$)&' !%MATLAB and Copasi are used in systems
biology research. I hope integrate these tools
in my own research to better understand thenetworks of breast cancer.
I had the opportunity to present a talkemphasizes the current issues of quantificationin biomarkers, entitled “Biomarker’s role in theearly detection of clinically significantcancer—Is it properly quantified?” on 26
November 2013. The current viewpoint is thatbiomarkers are vital for disease detection invarious clinical stages. Till date, a variety ofcancer serum biomarkers have been proposed,
yet for more accurate detection of thecancer-type and cancer-stage, several issues
need to be considered, the most important being the quantitative evaluation methods ofbiomarkers. In the talk, I discussed thepresent biomarker usages under the fiveclinical stages (FDA approval methodology)
developed by the National Cancer (Diagram3), was followed by introducing current
computational biomarker evaluation methods,
including ROC Curves and diagnostic odds
ratios (DOR) with its intrinsic problems. ThenI briefly discussed a current list of existing
cancer serum biomarkers, pointing out thepresent issues, mainly caused by thelimitations of the current biomarker
evaluation approaches. Finally, I discussed
the possibility of developing new cancer
evaluation approaches, which may be morestatistically robust compared to the current
methods in terms of the specificity of eachcancer type.

Finally, I would like to thank the Program
Director: Professor Hiroshi Mamitsuka for
guiding me the preparation process and for givingme the opportunity for s wonderful and valuable
research experience. I would also like to thank Professor Edda Klipp for accepting me to study
and work with such skilled researchers and for her guidance throughout the program. Last
but not least, I would like to thank the lab members of Klipp’s lab for all their help regarding
to technical problems in and out of the lab.
During my stay in Edda Klipp Lab, I was also able to take advantage of the rich cultural art
life in Berlin. Visiting the various famous museums and exhibitions such as the Pergamon
Museum, Altes Museum, Dali Exhibition, and the Picasso Exhibition, I was able toconceptualize history facts and events into reality, and enjoy the traditions and artistic
expression that resides throughout the city.
Description of pictures (Left to Right): 1. Berlin Wall Remembrance in Potzdamer Platz 2.
Brandenburg Gate during the Festival of Lights exhibition 3. The iconic Christmas tree
displayed in Gendarmenmarkt Weihnachtsmarkt (Gendarmenmarkt Christmas Market) 4.
Egyptian exhibition in the Altes Museum 5. Hotel De Rome during the Festival of Lights
exhibition 6. Charlottenburg Palace during the Weihnachtsmarkt

*"&'((ITP),+#$)&' !%Description of pictures (Left to Right): 1. Hotel De Rome during the Festival of Lights
exhibition 2. Egyptian exhibition in the Altes Museum 3. Brandenburg Gate during theFestival of Lights exhibition 4. Charlottenburg Palace during the Weihnachtsmarkt 5. The
iconic Christmas tree displayed in Gendarmenmarkt Weihnachtsmarkt (GendarmenmarktChristmas Market) 6. Berlin Wall Remembrance in Potzdamer Platz

Finally, I was able to engulf the free eclectic culture of the Germans to broaden myhorizons in my research and life, in general.
Artistic Expression through Music and Dance in Eberswalder Strasse Park

Vielen Dank für dieses Erlebnis.
(Thank you for this experience.)
References:Funahashi, A., Tanimura, N., Morohashi, M., and Kitano, H. (2003) “CellDesigner: a process
diagram editor for gene-regulatory and biochemical networks.” BIOSILICO 1:159-162.
Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P.,
and Kummer, U. (2006). “COPASI — a COmplex PAthway SImulator.” Bioinformatics 22,3067-74, doi:10.1093/bioinformatics/btl485.
Fuzery, AK, Levin J, Chan MM, Chan DW (2013) Translation of proteomic biomarkers into
FDA approved cancer diagnostics: issues and challenges. Clinical Proteomics. 10:13. doi:
http://www.clinicalproteomicsjournal.com/content/10/1/13.
Klipp, E. (2013) ‘Modellierung biologischer Systeme.’ Fachkurs Theoretische Biophysik,

*"&'((ITP)

,+#$)&' !%Humboldt University, Berlin November 19th to 29th. Humboldt University TheoretischeBiophysik.
Kumar M, Sarin SK. (2009)"Biomarkers of diseases in medicine.”
Current Trends of Science Platinum Jubilee Special, Indian Academy of Sciences: 403-17.
Reed MC, Nijhout HF, Neuhouser ML, Gregory JF III, James SJ, Boynton A, UlrichCM.(2006) “A mathematical model gives insights into nutritional and genetic aspects offolate-mediated one-carbon metabolism.” J Nutr 136 (10):2653-61.