| dc.date.accessioned |
2014-03-18T12:24:44Z |
und |
| dc.date.accessioned |
2017-10-24T12:23:40Z |
|
| dc.date.available |
2014-03-18T12:24:44Z |
und |
| dc.date.available |
2017-10-24T12:23:40Z |
|
| dc.date.issued |
2014-03-18T12:24:44Z |
|
| dc.identifier.uri |
http://radr.hulib.helsinki.fi/handle/10138.1/3556 |
und |
| dc.identifier.uri |
http://hdl.handle.net/10138.1/3556 |
|
| dc.title |
Evaluation of Comparative Metabolic Network Reconstruction |
en |
| ethesis.discipline |
Computer science |
en |
| ethesis.discipline |
Tietojenkäsittelytiede |
fi |
| ethesis.discipline |
Datavetenskap |
sv |
| ethesis.discipline.URI |
http://data.hulib.helsinki.fi/id/1dcabbeb-f422-4eec-aaff-bb11d7501348 |
|
| ethesis.department.URI |
http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14 |
|
| ethesis.department |
Institutionen för datavetenskap |
sv |
| ethesis.department |
Department of Computer Science |
en |
| ethesis.department |
Tietojenkäsittelytieteen laitos |
fi |
| ethesis.faculty |
Matematisk-naturvetenskapliga fakulteten |
sv |
| ethesis.faculty |
Matemaattis-luonnontieteellinen tiedekunta |
fi |
| ethesis.faculty |
Faculty of Science |
en |
| ethesis.faculty.URI |
http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca |
|
| ethesis.university.URI |
http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97 |
|
| ethesis.university |
Helsingfors universitet |
sv |
| ethesis.university |
University of Helsinki |
en |
| ethesis.university |
Helsingin yliopisto |
fi |
| dct.creator |
Hou, Jian |
|
| dct.issued |
2014 |
|
| dct.language.ISO639-2 |
eng |
|
| dct.abstract |
Pichia pastoris and Saccharomyces cerevisiae are two important fungi in both research and industrial applications of protein production and genetic engineering due to the inherent ability. For example, S.cerevisiae can produce important proteins from wide ranged sugar from ligno-cellulose to methanol. Accurate genome-scale metabolic networks (GMNs) of the two fungi can improve biotechnological production efficiency, drug discovery and cancer research. Comparison of metabolic networks between fungi brings a new way to study the evolutionary relationship between them.
There are two basic steps for modeling metabolic networks. The first step is to construct a draft model from existing model or softwares such as the pathway tool software and InterProScan. The second step is model simulation in order to construct a gapless metabolic network. There are two main methods for genome-wide metabolic network reconstruction: constraint-based methods and graph-theoretical pathway finding methods. Constraints-based methods used linear equations to simulate the growth under your model with different constraints. Graph-theoretical pathway finding methods use graphic approach to construct the gapless model so that each metabolite can be acquired from either nutritions or the products of other gapless reactions.
In my thesis, a new method designed by Pitkänen [PJH+ 14] is used to reconstruct the metabolic networks of Pichia pastoris and Saccharomyces cerevisiae. Five experiments were developed to evaluate the accuracy of the CoReCo method. The first experiment was to analyze the quality of the GMNs of Pichia pastoris and Saccharomyces cerevisiae by comparing with the existing model. The second and third experiments tested the stability of CoReCo constructed under random mutation and random deletion of the protein sequence simulating noisy input data. The next two experiments were done by considering different number of phylogenetic neighbors in the phylogenetic tree. The last experiment tested the effect of the two main parameters (acceptance and rejection thresholds) when CoReCo filled the reaction gaps in the final step. |
en |
| dct.language |
en |
|
| ethesis.language.URI |
http://data.hulib.helsinki.fi/id/languages/eng |
|
| ethesis.language |
English |
en |
| ethesis.language |
englanti |
fi |
| ethesis.language |
engelska |
sv |
| ethesis.thesistype |
pro gradu-avhandlingar |
sv |
| ethesis.thesistype |
pro gradu -tutkielmat |
fi |
| ethesis.thesistype |
master's thesis |
en |
| ethesis.thesistype.URI |
http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis |
|
| ethesis.degreeprogram |
Bioinformatics |
en |
| dct.identifier.urn |
URN:NBN:fi-fe2017112251722 |
|
| dc.type.dcmitype |
Text |
|
