Novel gene sets improve set-level classification of prokaryotic gene expression data

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fuzzy Soft Set Based Classification for Gene Expression Data

Abstract — Classification is one of the major issues in Data Mining Research fields. The classification problems in medical area often classify medical dataset based on the result of medical diagnosis or description of medical treatment by the medical practitioner. This research work discusses the classification process of Gene Expression data for three different cancers which are breast cancer...

متن کامل

A Novel Feature Selection Method to Improve Classification of Gene Expression Data

This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximise the classification accuracy. The method uses a hybrid of Pearson correlation coefficient (PCC) and signal-to-noise ratio (SNR) methods combined with an evolving classification function (ECF). First, the correlation ...

متن کامل

Locally linear embedding and neighborhood rough set-based gene selection for gene expression data classification.

Cancer subtype recognition and feature selection are important problems in the diagnosis and treatment of tumors. Here, we propose a novel gene selection approach applied to gene expression data classification. First, two classical feature reduction methods including locally linear embedding (LLE) and rough set (RS) are summarized. The advantages and disadvantages of these algorithms were analy...

متن کامل

Classification 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 کامل

Interpreting Gene Expression Data by Searching for Enriched Gene Sets

This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment of a gene set is determined by Gene Set Enrichment Analysis, which is a microarray data analysis method that uses ranks of the genes, according to their differentially expression values, to identify significant biologi...

متن کامل

ذخیره 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: BMC Bioinformatics

سال: 2015

ISSN: 1471-2105

DOI: 10.1186/s12859-015-0786-7