Please use this identifier to cite or link to this item:
https://lib.hpu.edu.vn/handle/123456789/22288
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Grolmusz, Vince I. | en_US |
dc.date.accessioned | 2016-07-18T06:49:10Z | |
dc.date.available | 2016-07-18T06:49:10Z | |
dc.date.issued | 2015 | en_US |
dc.identifier.other | HPU4160444 | en_US |
dc.identifier.uri | https://lib.hpu.edu.vn/handle/123456789/22288 | en_US |
dc.description.abstract | Diabetes is a growing concern for the developed nations worldwide. New genomic, metagenomic and gene-technologic approaches may yield considerable results in the next several years in its early diagnosis, or in advances in therapy and management. In this work, we highlight some human proteins that may serve as new targets in the early diagnosis and therapy. With the help of a very successful mathematical tool for network analysis that formed the basis of the early successes of GoogleTM we analyse the human protein–protein interaction network gained from the IntAct database with a mathematical algorithm. | en_US |
dc.format.extent | 8 p. | en_US |
dc.format.mimetype | application/pdf | en_US |
dc.language.iso | en | en_US |
dc.subject | Computer science | en_US |
dc.subject | Bioinformatics | en_US |
dc.subject | Computational biology | en_US |
dc.subject | Protein interaction database | en_US |
dc.subject | Interactome | en_US |
dc.subject | Relativized | en_US |
dc.subject | PageRank | en_US |
dc.title | Identifying diabetes-related important protein targets with few interacting partners with the PageRank algorithm | en_US |
dc.type | Article | en_US |
dc.size | 327KB | en_US |
dc.department | Education | en_US |
Appears in Collections: | Education |
Files in This Item:
File | Description | Size | Format | |
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0327_Identifyingdiabetesrelatedimportant.pdf Restricted Access | 327.34 kB | Adobe PDF | ![]() View/Open Request a copy |
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