Open AccessCancer Prediction with Gene Expression Data
Author(s) -
G Sivagamasundari,
Latha Parthiban,
Anirban Mukhopadhyay,
I Balasundar,
Evgeniy Raju,
Ralf Leyvi,
Seip,
Andrew Shriram Sethuraman,
Songtao Bird,
Dwight Li,
Koberi,
Bharathi And Dr,
Natarajan,
Colin Molter,
Robin Duque,
Hugues Bersini,
Ann Nowe,
Dimitris Maroulis,
Dimitris Iakovidis,
Ilias Flaounas,
Stavros Karkanis
Publication year - 2019
Publication title -
international journal of recent technology and engineering (ijrte)
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1050.0782s419
Subject(s) - cluster analysis , data mining , expression (computer science) , computer science , cluster (spacecraft) , gene , cancer , artificial intelligence , biology , genetics , programming language
With continuous growth in technology and quantum of data, many data mining algorithms are developed that uses micro array data to classify the genes and expressions in normal and disease conditions. There are many clustering algorithms that help to classify the genes and there is conflict in large pool of genes and their expression characters. The proposed system takes the input from multiple sources produces associate storage, cluster the information and classify it.
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