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Clustering genes using gene expression and text literature data
2005 IEEE Computational Systems Bioinformatics Conference (CSB'05), 2005Clustering of gene expression data is a standard technique used to identify closely related genes. In this paper, we develop a new clustering algorithm, MSC (Multi-Source Clustering), to perform exploratory analysis using two or more diverse sources of data.
Chengyong, Yang +3 more
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Gene expression microarray data analysis demystified
2008The increasing use of gene expression microarrays, and depositing of the resulting data into public repositories, means that more investigators are interested in using the technology either directly or through meta analysis of the publicly available data.
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An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne Penberthy +2 more
exaly
Innovations in research and clinical care using patient‐generated health data
Ca-A Cancer Journal for Clinicians, 2020H S L Jim +2 more
exaly
Integrative Gene Selection on Gene Expression Data
2019The advance of high-throughput RNA-Sequencing techniques enables researchers to analyze the complete gene activity in particular cells. From the insights of such analyses, researchers can identify disease-specific expression profiles, thus understand complex diseases like cancer, and eventually develop effective measures for diagnosis and treatment ...
Perscheid, Cindy (Dr.) +2 more
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Exploiting Gene-Expression Data
Genetic Engineering & Biotechnology News, 2012openaire +1 more source