Malaysian Applied Biology Journal

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46_04_16

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Malays. Appl. Biol. (2017) 46(4): 137–143

CURATING SBGN BASED METABOLIC MAP AND COMPARATIVE

ASSESSMENT ON PUBLISHED SUGAR METABOLIC PATHWAYS

IN ONLINE DATABASES

 

MUHAMAD ASRUL FAIZ MOHD KHALIM, AIZUL SHAZRIL MOHAMAD MANGIN,

NURAQILAH YUSRA RAHEMAN, GOH MEG SHIEN and

MUHAMAD FAIRUS NOOR HASSIM*

 

School of Fundamental Science, Universiti Malaysia Terengganu,

21030 Kuala Nerus, Terengganu, Malaysia


*Email: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Accepted 23 November 2017, Published online 31 December 2017

 

ABSTRACT

Mapping and illustration of biochemical interaction pathways have been used by the molecular biologist for decades to describe cellular processes. The effort in mapping these molecular interactions comes in myriad of forms, lacks standardisation and most of the annotated maps are not computer readable. Recent years, efforts have been made in standardising mapping processes and also to be computer readable. This include standardise notation and development of standard language that are readable across platforms. We assessed variability of the published sugar metabolic map available in Recon2, KEGG, HumanCyc and EcoCyc. Sets of molecular interaction and maps of metabolic pathways were extracted from these databases and revisualised using System Biology Graphical Notation (SBGN) in VANTED. Variabilities were assessed based on differences in the annotation, nodes (components) and edges (reactions). Our study identifies two key issues, the variability in the data visualisation and variability in the number of registered nodes and edges across databases for human and E. coli metabolic pathways. Variation in the visualisation rooted from differences in the curated nodes and edges and also may due to each database has taken different approaches and philosophies in establishing the molecular interaction thus affecting the detail in molecular interaction.

Key words: System Biology Graphical Notation (SBGN), KEGG, HumanCyc, EcoCyc, Recon2, mapping, carbohydrate

 

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