Gene expression based cancer classification
نویسندگان
چکیده
منابع مشابه
Gene Expression Based Cancer Classification
Gene expression profiles were shown to be useful in genomic signal processing when discriminating between cancer and normal (healthy) examples and/or between different types of cancer. K-nearest neighbors (k-NN) is one of the classification algorithms that demonstrated good performance for gene expression based cancer classification. Given that distance metric is fixed, the conventional k-NN ha...
متن کاملSFLA Based Gene Selection Approach for Improving Cancer Classification Accuracy
In this paper, we propose a new gene selection algorithm based on Shuffled Frog Leaping Algorithm that is called SFLA-FS. The proposed algorithm is used for improving cancer classification accuracy. Most of the biological datasets such as cancer datasets have a large number of genes and few samples. However, most of these genes are not usable in some tasks for example in cancer classification....
متن کاملGene boosting for cancer classification based on gene expression profiles
Article history: Received 11 February 2008 Received in revised form 12 November 2008 Accepted 7 January 2009
متن کاملClassification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and smal...
متن کاملRandom Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classification based on gene expression and address two issues that have been so far overlooked in other works. First, we demonstrate on two different real-world datasets that the performance of random forest is strongly influe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2017
ISSN: 1110-8665
DOI: 10.1016/j.eij.2016.12.001