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Network Biology, 2018, 8(3): 113-125
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Article

Investigate to find common gene and design a PPI network for vector borne diseases (Malaria, Dengue and Chikungunya) ¨C A bioinformatics approach

Tanjina Akter1, Lubna Yasmin Pinky1, Md. Mosaddik Hasan1, Farzana Akter Chowdhury2, Md. Imam Hossain3
1Department of Computer Science and Engineering (CSE), MawlanaBhashani Science and Technology University (MBSTU), Santosh, Tangail-1902, Bangladesh
2Department of Computer Science and Engineering (CSE), University of South Asia, Banani, Dhaka, Bangladesh
3Department of Biotechnology and Genetic Engineering (BGE), MawlanaBhashani Science and Technology University (MBSTU), Santosh, Tangail-1902, Bangladesh

Received 22 March 2018;Accepted 30 April 2018;Published 1 September 2018
IAEES

Abstract
Malaria, Dengue and Chikungunya are the most common mosquito-borne viral diseases transmitted to humans by day-biting Aedes aegypti and Aedes albopictus mosquitoes. Different types of gene are responsible for these viruses. The principal study of this research is to find the relationship between genetic variant for these three diseases and to create a common pathway regulatory or Protein-Protein Interaction (PPI) network. Our investigation goes through preprocessing, filtering, sorting and gene mining on the gathered gene (Malaria, Dengue and Chikungunya) using R to find the common associated genes by the process of reduction. The investigation shows that about 60% of the collected gene from different standard gene database is responsible for animal virus attack. After preprocessing, filtering and sorting using R toolkit, the number of collected gene for three diseases (A=malaria, B=dengue and C=chikunguniya) is reduced to 35%. Gene mining is done by intersection operation on (A, B), (B, C) and (C, A) that reduces the common associated gene from 35% to 5%. Finally, the reduction is done by intersecting AB, BC and CA that reduces the common gene from 5% to less than 1%. We have discovered five (5) common associated genes for these three virus diseases. However a common pathway with the five (5) common associated genes that has been designed for selective diseases.

Keywords malaria;dengue;chikungunya;data mining;PPI network;R toolkit;NCBI;UniHi.



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