13 papers · ranked by Valyu relevance
Nikita Bhandari, Rahee Walambe, Ketan Kotecha, Satyajeet P. Khare
Computational analysis methods including machine learning have a significant impact in the fields of genomics and medicine. High-throughput gene expression analysis methods such as microarray technology and RNA sequencing produce enormous amounts of data. Traditionally, statistical methods are used for comparative…
Mohsen Hajiloo, Hamid R Rabiee, Mahdi Anooshahpour
Background The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and…
Jingeun Kim, Yourim Yoon, Hye-Jin Park, Yong-Hyuk Kim + 1 more
Microarrays are applications of electrical engineering and technology in biology that allow simultaneous measurement of expression of numerous genes, and they can be used to analyze specific diseases. This study undertakes classification analyses of various microarrays to compare the performances of classification…
Thanh Nguyen, Abbas Khosravi, Douglas Creighton, Saeid Nahavandi + 1 more
'Enrique Hernandez-Lemus'] This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five…
Maryam Eshraghi Evari, Md. Nasir Sulaiman, Amir Behjat
Data Authors: ['Maryam Eshraghi Evari' 'Md. Nasir Sulaiman' 'Amir Behjat'] DNA microarray gene-expression data has been widely used to identify cancerous gene signatures. Microarray can increase the accuracy of cancer diagnosis and prognosis. However, analyzing the large amount of gene expression data from microarray…
R Simon
DNA microarrays are a potentially powerful technology for improving diagnostic classification, treatment selection and therapeutics development. There are, however, many potential pitfalls in the use of microarrays that result in false leads and erroneous conclusions. This paper provides a review of the key features to…
Jaison Bennet, Chilambuchelvan Arul Ganaprakasam, Kannan Arputharaj
Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in…
Mrutyunjaya Panda
Gene is the basic unit of storage containing hereditary information in living beings. For the technical point of view,it can be treated as a distinct sequence of nucleotides constituting part of a chromosome. Microarrays data analysis is relatively a new technology that aims to help in finding the right treatment for…
Min Xu, Rudy Setiono
Various approaches to gene selection for cancer classification based on microarray data can be found in the literature and they may be grouped into two categories: univariate methods and multivariate methods. Univariate methods look at each gene in the data in isolation from others. They measure the contribution of a…
Ajin R. Nair, Harikumar Rajaguru, M. S. Karthika, C. Keerthivasan
The microarray gene expression data poses a tremendous challenge due to their curse of dimensionality problem. The sheer volume of features far surpasses available samples, leading to overfitting and reduced classification accuracy. Thus the dimensionality of microarray gene expression data must be reduced with…
Khalid Raza
Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more prevalent, the challenges of analyzing these data for getting better insight about…
Nikita Bhandari, Rahee Walambe, Ketan Kotecha, Satyajeet P. Khare
Computational analysis methods including machine learning have a significant impact in the fields of genomics and medicine. High-throughput gene expression analysis methods such as microarray technology and RNA sequencing produce enormous amounts of data. Traditionally, statistical methods are used for comparative…
Xiaohui Yang, Li Tian, Yunmei Chen, Lijun Yang + 2 more
'Wenming Wu'] Abstract—Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse projection representation based…