TY - GEN
T1 - A direct proof of improved biased random walk with gastric cancer dataset
AU - Seah, Choon Sen
AU - Kasim, Shahreen
AU - Fudzee, Mohd Farhan Md
AU - Mohamad, Mohd Saberi
AU - Saedudin, Rd Rohmat
AU - Witarsyah, Deden
AU - Hassan, Rohayanti
AU - Ismail, Mohd Arfian
AU - Atan, Rodziah
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4
Y1 - 2018/4
N2 - The relationship between the weight of a single genes and the connection between the genes had been studied. Chemistry and physical sciences have proved the attraction between molecules. Molecules are attracted to each other by bond. This paper is presented to disclose the relationship between weight and connectivity of nodes with biased random walk. An equation of biased random walk which named as significant directed random walk is formed to enhance the connectivity of nodes in directed graph via weigh. To be completely biased to the random walk, references data is implement as directed graph. Weight of genes will be used as one of the parameter in the formula. While the adjacency matrix is further enhanced by Warshall's algorithm to increases the accessibility of nodes via vector. The evolution of random walk is disclosed in this paper as well. Significant directed random walk will be used to prove the importance of weight in this paper. Comparison of the result between biased random walk is presented to prove the enhancement of random walk.
AB - The relationship between the weight of a single genes and the connection between the genes had been studied. Chemistry and physical sciences have proved the attraction between molecules. Molecules are attracted to each other by bond. This paper is presented to disclose the relationship between weight and connectivity of nodes with biased random walk. An equation of biased random walk which named as significant directed random walk is formed to enhance the connectivity of nodes in directed graph via weigh. To be completely biased to the random walk, references data is implement as directed graph. Weight of genes will be used as one of the parameter in the formula. While the adjacency matrix is further enhanced by Warshall's algorithm to increases the accessibility of nodes via vector. The evolution of random walk is disclosed in this paper as well. Significant directed random walk will be used to prove the importance of weight in this paper. Comparison of the result between biased random walk is presented to prove the enhancement of random walk.
KW - Biased random walk
KW - Cancer classification
KW - Gene expression dataset
UR - http://www.scopus.com/inward/record.url?scp=85078905844&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078905844&partnerID=8YFLogxK
U2 - 10.1109/ICAMCS46079.2018.000-2
DO - 10.1109/ICAMCS46079.2018.000-2
M3 - Conference contribution
AN - SCOPUS:85078905844
T3 - Proceedings - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
SP - 28
EP - 34
BT - Proceedings - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
Y2 - 13 April 2018 through 15 April 2018
ER -
