Name
Title | ||
|---|---|---|
Predicting functional elements and variants effects in non-coding regions based on deep learning |
Abstract | ||
|---|---|---|
Accurate recognition and annotation of the important functional elements in the genome is an important prerequisite to understand the coding mode of complex regulatory networks in the one-dimensional genome. Despite rapid advances in sequencing and recognition technologies, accurately calling non-coding variant effects from large-scale sequence reads remains challenging. Here we present a deep neu... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/HEALTHCOM49281.2021.9398970 | 2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM) |
Keywords | DocType | ISBN |
Sequential analysis,Biological system modeling,Genomics,Predictive models,Epigenetics,Data models,Bioinformatics | Conference | 978-1-7281-6267-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunhao Liu | 1 | 8810 | 486.66 |
| Shaoliang Peng | 2 | 0 | 1.69 |
| Wenjie Shu | 3 | 0 | 0.34 |
| Bin Jiang | 4 | 0 | 0.68 |
| Chao Yang | 5 | 87 | 22.49 |
| Kun Xie | 6 | 0 | 0.34 |