| Chapter title |
Inferring Genome-Wide Interaction Networks.
|
|---|---|
| Chapter number | 6 |
| Book title |
Bioinformatics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6613-4_6 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6611-0, 978-1-4939-6613-4
|
| Authors |
Gökmen Altay, Onur Mendi |
| Editors |
Jonathan M. Keith |
| Abstract |
The inference of gene regulatory networks is an important process that contributes to a better understanding of biological and biomedical problems. These networks aim to capture the causal molecular interactions of biological processes and provide valuable information about normal cell physiology. In this book chapter, we introduce GNI methods, namely C3NET, RN, ARACNE, CLR, and MRNET and describe their components and working mechanisms. We present a comparison of the performance of these algorithms using the results of our previously published studies. According to the study results, which were obtained from simulated as well as expression data sets, the inference algorithm C3NET provides consistently better results than the other widely used methods. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 80 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 24% |
| Student > Ph. D. Student | 14 | 18% |
| Student > Master | 10 | 13% |
| Student > Bachelor | 7 | 9% |
| Professor | 4 | 5% |
| Other | 11 | 14% |
| Unknown | 15 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 26% |
| Biochemistry, Genetics and Molecular Biology | 21 | 26% |
| Chemistry | 3 | 4% |
| Arts and Humanities | 2 | 3% |
| Physics and Astronomy | 2 | 3% |
| Other | 10 | 13% |
| Unknown | 21 | 26% |