TY - GEN
T1 - GCLUPS
T2 - 2013 International Conference of Information and Communication Technology, ICoICT 2013
AU - Yulita, Intan Nurma
AU - Wasito, Ito
AU - Mujiono,
PY - 2013
Y1 - 2013
N2 - The development of bioinformatics has depended on the contributions of many experts in the various disciplines, such as biologists, chemist, computer scientists, and mathematicians. One of the most widely discussed cases in bioinformatics is the protein grouping. Proteins work together each other to regulate a biological process. From computer science point of view, the interactions that occur between proteins will form a graph, and a mechanism of grouping is done by a unique process, namely clustering. Clustering will be done based on graph of protein interactions. Therefore, this study discusses about a new method that includes in graph clustering. The mechanism is made based on the similarity of protein pairs. If a pair of proteins has high similarity then they will be in the same cluster, and vice versa. As evaluation, this method is implemented on a network of protein domain and compared with grPartition, a well known method for graph clustering. The results show that gCLUPS has a better performance than grPartition in connectivity and separation but not homogeneity.
AB - The development of bioinformatics has depended on the contributions of many experts in the various disciplines, such as biologists, chemist, computer scientists, and mathematicians. One of the most widely discussed cases in bioinformatics is the protein grouping. Proteins work together each other to regulate a biological process. From computer science point of view, the interactions that occur between proteins will form a graph, and a mechanism of grouping is done by a unique process, namely clustering. Clustering will be done based on graph of protein interactions. Therefore, this study discusses about a new method that includes in graph clustering. The mechanism is made based on the similarity of protein pairs. If a pair of proteins has high similarity then they will be in the same cluster, and vice versa. As evaluation, this method is implemented on a network of protein domain and compared with grPartition, a well known method for graph clustering. The results show that gCLUPS has a better performance than grPartition in connectivity and separation but not homogeneity.
KW - bioinformatics
KW - graph clustering
KW - pairwise similarity
KW - protein
UR - http://www.scopus.com/inward/record.url?scp=84883470629&partnerID=8YFLogxK
U2 - 10.1109/ICoICT.2013.6574553
DO - 10.1109/ICoICT.2013.6574553
M3 - Conference contribution
AN - SCOPUS:84883470629
SN - 9781467349925
T3 - 2013 International Conference of Information and Communication Technology, ICoICT 2013
SP - 77
EP - 81
BT - 2013 International Conference of Information and Communication Technology, ICoICT 2013
Y2 - 20 March 2013 through 22 March 2013
ER -