| Chapter title |
MPFit: Computational Tool for Predicting Moonlighting Proteins
|
|---|---|
| Chapter number | 5 |
| Book title |
Protein Function Prediction
|
| Published in |
Methods in molecular biology, April 2017
|
| DOI | 10.1007/978-1-4939-7015-5_5 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7013-1, 978-1-4939-7015-5, 978-1-4939-7013-1, 978-1-4939-7015-5
|
| Authors |
Ishita Khan, Joshua McGraw, Daisuke Kihara, Khan, Ishita, McGraw, Joshua, Kihara, Daisuke |
| Editors |
Daisuke Kihara |
| Abstract |
An increasing number of proteins have been found which are capable of performing two or more distinct functions. These proteins, known as moonlighting proteins, have drawn much attention recently as they may play critical roles in disease pathways and development. However, because moonlighting proteins are often found serendipitously, our understanding of moonlighting proteins is still quite limited. In order to lay the foundation for systematic moonlighting proteins studies, we developed MPFit, a software package for predicting moonlighting proteins from their omics features including protein-protein and gene interaction networks. Here, we describe and demonstrate the algorithm of MPFit, the idea behind it, and provide instruction for using the software. |
X Demographics
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|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 30% |
| Student > Bachelor | 1 | 10% |
| Student > Ph. D. Student | 1 | 10% |
| Professor | 1 | 10% |
| Student > Master | 1 | 10% |
| Other | 1 | 10% |
| Unknown | 2 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 60% |
| Agricultural and Biological Sciences | 2 | 20% |
| Unknown | 2 | 20% |