| Chapter title |
BiNGS!SL-seq: A Bioinformatics Pipeline for the Analysis and Interpretation of Deep Sequencing Genome-Wide Synthetic Lethal Screen.
|
|---|---|
| Chapter number | 26 |
| Book title |
Next Generation Microarray Bioinformatics
|
| Published in |
Methods in molecular biology, January 2012
|
| DOI | 10.1007/978-1-61779-400-1_26 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-399-8, 978-1-61779-400-1
|
| Authors |
Jihye Kim, Aik Choon Tan, Kim, Jihye, Tan, Aik Choon |
| Abstract |
While targeted therapies have shown clinical promise, these therapies are rarely curative for advanced cancers. The discovery of pathways for drug compounds can help to reveal novel therapeutic targets as rational combination therapy in cancer treatment. With a genome-wide shRNA screen using high-throughput genomic sequencing technology, we have identified gene products whose inhibition synergizes with their target drug to eliminate lung cancer cells. In this chapter, we described BiNGS!SL-seq, an efficient bioinformatics workflow to manage, analyze, and interpret the massive synthetic lethal screen data for finding statistically significant gene products. With our pipeline, we identified a number of druggable gene products and potential pathways for the screen in an example of lung cancer cells. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 5% |
| Denmark | 1 | 5% |
| Unknown | 17 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 37% |
| Student > Ph. D. Student | 4 | 21% |
| Professor | 3 | 16% |
| Professor > Associate Professor | 3 | 16% |
| Student > Doctoral Student | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 42% |
| Biochemistry, Genetics and Molecular Biology | 5 | 26% |
| Medicine and Dentistry | 3 | 16% |
| Social Sciences | 1 | 5% |
| Computer Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 1 | 5% |