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In a Gene Co-expression Network, the same or closely related genes are clustered into co-expressed groups. It is necessary to investigate the role that these genes play as far as some complex diseases like cancer are concerned in those networks. Ranking those genes actually discover the significant candidate genes for various types of cancers. There are several gene ranking algorithms proposed so ...Show More
A novel SFLA based method for gene expression biclustering
2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)
Year: 2017 | Conference Paper |
Form the time of its invention, microarray technology is continuously growing and has been taking major role in biological research. This technology generates huge amount of gene expression data for biological analysis. Parallel computation methods are required to find functional associations from this large amount of biological data. An unsupervised machine learning technique, clustering algorith...Show More
An ensemble based missing value estimation in DNA microarray using artificial neural network
2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)
Year: 2016 | Conference Paper |
Cited by: Papers (1)
DNA microarrays are normally used to measure the expression values of thousands of several genes simultaneously in the form of large matrices. This raw gene expression data may contain some missing cells. These missing values may affect the analysis performed subsequently on these gene expression data. Several imputation methods, like K-Nearest Neighbor Imputation (KNNImpute), Singular Value Decom...Show More
Gene — Gene Interaction: A clustering, correlation & entropy based approach
Dibyendu Bikash Seal;Sujay Saha;Mayukh Chatterjee;Prokriti Mukherjee;Aradhita Mukherjee;Bipasha Mukhopadhyay;Sohini Mukherjee
2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
Gene - Gene Interaction is a logical interaction between two genes that affects the observable behavior of one organism. This genetic interaction helps to identify pathways of associated genes for various diseases. In this paper we have used two metrics, like correlation & entropy to find the level of interaction between the genes applied on Gene Interaction networks. We have applied our algorithm...Show More
Gene ranking: An entropy & decision tree based approach
Dibyendu Bikash Seal;Sujay Saha;Prokriti Mukherjee;Mayukh Chatterjee;Aradhita Mukherjee;Kashi Nath Dey
2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Year: 2016 | Conference Paper |
Cited by: Papers (3)
The Cancer disease involves abnormal cell growth and has the potential to spread to other parts of the body. Today, technology has provided us with many methods to study the pattern of thousands of cancer gene expressions simultaneously. Often microarray gene expression data comprises of a huge number of genes and a very small number of samples or observations. Our task is to identify those genes ...Show More
An improved fuzzy based approach to impute missing values in DNA microarray gene expression data with collaborative filtering
2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Year: 2016 | Conference Paper |
Cited by: Papers (5)
DNA microarray experiments normally generate gene expression profiles in the form of high dimensional matrices. It may happen that DNA microarray gene expression values contain many missing values within its data due to several reasons like image disruption, hybridization error, dust, moderate resolution etc. It will be very unfortunate if these missing values affect the performance of subsequent ...Show More
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