TY - GEN
T1 - A biclustering procedure using BicBin algorithm for HIV-1 human protein interaction database in NCBI
AU - Tampubolon, Patuan Pangihutan
AU - Bustamam, Alhadi
AU - Lestari, Dian
AU - Mangunwardoyo, Wibowo
N1 - Publisher Copyright:
© 2019 Author(s).
PY - 2019/3/22
Y1 - 2019/3/22
N2 -
The objective of establishing the HIV-1 Human Interaction Database (HHPID) in the NCBI that is to encourage the scientists to produce more publications. The database collates two types of interactions from the published reports - protein in- teractions and replication interactions. One of the growing up data mining technique is bioinformatics is biclustering. The BicBin algorithm is one of the biclustering method to a binary matrix. We propose a systematic procedure to make biclusters to the HHPID using BicBin algorithm. First, we select the HIV-1 proteins, the human proteins, and the interaction keywords from HHPID to model the interaction as a bipartite graph. The Keywords are divided into three classes based on the direction of the interactions and then separated them into two binary matrices, i.e., positive and negative matrix. The binary matrices then become the input to the BicBin algorithm. The algorithm outputs many biclusters. The user sets the input parameter α and β to control the search area in each binary matrix. The parameter p
1
is used to control the density of the biclusters. Then, the algorithm is iterated by parameter I. We set α = 0.5, β = 0.5, p
1
= 1, and I = 600 in our procedure.
AB -
The objective of establishing the HIV-1 Human Interaction Database (HHPID) in the NCBI that is to encourage the scientists to produce more publications. The database collates two types of interactions from the published reports - protein in- teractions and replication interactions. One of the growing up data mining technique is bioinformatics is biclustering. The BicBin algorithm is one of the biclustering method to a binary matrix. We propose a systematic procedure to make biclusters to the HHPID using BicBin algorithm. First, we select the HIV-1 proteins, the human proteins, and the interaction keywords from HHPID to model the interaction as a bipartite graph. The Keywords are divided into three classes based on the direction of the interactions and then separated them into two binary matrices, i.e., positive and negative matrix. The binary matrices then become the input to the BicBin algorithm. The algorithm outputs many biclusters. The user sets the input parameter α and β to control the search area in each binary matrix. The parameter p
1
is used to control the density of the biclusters. Then, the algorithm is iterated by parameter I. We set α = 0.5, β = 0.5, p
1
= 1, and I = 600 in our procedure.
UR - http://www.scopus.com/inward/record.url?scp=85063894106&partnerID=8YFLogxK
U2 - 10.1063/1.5094272
DO - 10.1063/1.5094272
M3 - Conference contribution
AN - SCOPUS:85063894106
T3 - AIP Conference Proceedings
BT - Proceedings of the Symposium on BioMathematics, SYMOMATH 2018
A2 - Handari, Bevina Desjwiandra
A2 - Seno, Hiromi
A2 - Tasman, Hengki
PB - American Institute of Physics Inc.
T2 - International Symposium on BioMathematics 2018, SYMOMATH 2018
Y2 - 31 August 2018 through 2 September 2018
ER -
