Name
Title | ||
|---|---|---|
Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction. |
Abstract | ||
|---|---|---|
We compare the sets of genes obtained from the classifications on RNA sequencing and DNA methylation data with the genes obtained from the integration of the two experiments. The comparison results in several genes that are in common among the single experiments and the integrated ones (733 for BRCA, 35 for KIRP, and 861 for THCA) and 509 genes that are in common among the different experiments. Finally, we investigate the possible relationships among the different analyzed tumors by extracting a core set of 13 genes that appear in all tumors. A preliminary functional analysis confirms the relation of part of those genes (5 out of 13 and 279 out of 509) with cancer, suggesting to focus further studies on the new individuated ones. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13040-018-0184-6 | BioData Mining |
Keywords | Field | DocType |
Cancer,Classification,DNA methylation,Next generation sequencing,RNA sequencing | Genome,Biological data,RNA,Gene,Computer science,Gene expression,Methylation,DNA methylation,DNA sequencing,Bioinformatics,Computational biology | Journal |
Volume | Issue | ISSN |
11 | 1 | 1756-0381 |
Citations | PageRank | References |
1 | 0.37 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eleonora Cappelli | 1 | 5 | 3.17 |
| Giovanni Felici | 2 | 201 | 21.98 |
| Emanuel Weitschek | 3 | 84 | 10.63 |