Functional genomics, proteomics, metabolomics and bioinformatics for systems biology
S Ballereau, E Glaab, A Kolodkin… - … : Integrative Biology and …, 2013 - Springer
Abstract This chapter introduces Systems Biology, its context, aims, concepts and strategies,
then describes approaches used in genomics, epigenomics, transcriptomics, proteomics …
then describes approaches used in genomics, epigenomics, transcriptomics, proteomics …
[PDF][PDF] The elements of statistical learning in colon cancer datasets: data mining, inference and prediction
D Kaladhar, BK Pottumuthu, PVN Rao… - Algorithms …, 2013 - researchgate.net
Data mining is used in various medical applications like tumor classification, protein
structure prediction, gene classification, cancer classification based on microarray data …
structure prediction, gene classification, cancer classification based on microarray data …
Identification of glucocorticoid-regulated genes and inferring their network focused on the glucocorticoid receptor in childhood leukaemia, based on microarray data …
A Chaiboonchoe - 2010 - researcharchive.lincoln.ac.nz
Acute lymphoblastic leukaemia (ALL) has the highest mortality rate in childhood cancer.
Glucocorticoids (GCs) have been used as chemotherapeutic drugs for children with ALL for …
Glucocorticoids (GCs) have been used as chemotherapeutic drugs for children with ALL for …
[PDF][PDF] Hybrid Algorithm for Clustering of Microarray Data
Clustering is a crucial step in the analysis of gene expression data. Its goal is to identify the
natural clusters and provide a reliable estimate of the number of distinct clusters in a given …
natural clusters and provide a reliable estimate of the number of distinct clusters in a given …