Name
Title | ||
|---|---|---|
The Use Of Inductive Methods To Identify Subtypes Of Glioblastomas In Gene Clustering |
Abstract | ||
|---|---|---|
The article presents an inductive clustering model of RNA-seq data for solving the problem of identifying glioblastomas subtypes by inductive methods based on k- and c-means algorithms. Comparative studies between inductive and classical iterative clustering algorithms are carried out using the criteria for evaluating clustering and data visualization. The basic principles of creating an inductive model of objective clustering are formed, the ways and prospects of the possible implementation of the model are shown, the advantages of the objective clustering model in comparison with traditional methods of data clustering are determined. |
Year | Venue | Keywords |
|---|---|---|
2020 | MOMLET+DS 2020: MODERN MACHINE LEARNING TECHNOLOGIES AND DATA SCIENCE WORKSHOP | Inductive Modeling, Multiform Glioblastoma, Clustering of Biologist Objects, the Method of Group Accounting of Arguments, K-Means Algorithm, External Balance Criterion |
DocType | Volume | ISSN |
Conference | 2631 | 1613-0073 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iryna Lurie | 1 | 1 | 1.71 |
| Volodymyr Lytvynenko | 2 | 4 | 2.54 |
| Serge Olszewski | 3 | 0 | 1.01 |
| Mariia Voronenko | 4 | 1 | 2.04 |
| Alexander Kornelyuk | 5 | 0 | 0.34 |
| Ulzhalgas Zhunissova | 6 | 0 | 0.68 |
| Oleg Boskin | 7 | 1 | 1.03 |