TY - GEN
T1 - BicGenesis
T2 - International Conference on Big Data, Machine Learning and Applications, BigDML 2019
AU - Saikia, Manaswita
AU - Bhattacharyya, Dhruba K.
AU - Kalita, Jugal K.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.
PY - 2021
Y1 - 2021
N2 - Biclustering has already been established as an effective tool to study gene expression data toward interesting biomarker findings for a given disease. This paper examines the effectiveness of some prominent biclustering algorithms in extracting biclusters of high biological significance toward the identification of interesting biomarkers. We have chosen Esophageal Squamous Cell Carcinoma (ESCC) as a case for our empirical study and our method called BicGenesis could identify eight genes as possible biomarkers for ESCC.
AB - Biclustering has already been established as an effective tool to study gene expression data toward interesting biomarker findings for a given disease. This paper examines the effectiveness of some prominent biclustering algorithms in extracting biclusters of high biological significance toward the identification of interesting biomarkers. We have chosen Esophageal Squamous Cell Carcinoma (ESCC) as a case for our empirical study and our method called BicGenesis could identify eight genes as possible biomarkers for ESCC.
UR - https://www.scopus.com/pages/publications/85125116851
UR - https://www.scopus.com/inward/citedby.url?scp=85125116851&partnerID=8YFLogxK
U2 - 10.1007/978-981-33-4788-5_1
DO - 10.1007/978-981-33-4788-5_1
M3 - Conference contribution
AN - SCOPUS:85125116851
SN - 9789813347878
T3 - Lecture Notes in Networks and Systems
SP - 1
EP - 14
BT - Proceedings of International Conference on Big Data, Machine Learning and Applications, BigDML 2019
A2 - Patgiri, Ripon
A2 - Balas, Valentina Emilia
A2 - Bandyopadhyay, Sivaji
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 16 December 2019 through 19 December 2019
ER -