Population and clinical genetics of human transposable elements in the (post) genomic era-Reference-Cited by-同舟云学术

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Population and clinical genetics of human transposable elements in the (post) genomic era

Published:2017-01-02 Issue:1 Volume:7 Page:1-20
ISSN:2159-256X
Container-title:Mobile Genetic Elements
language:en
Short-container-title:Mobile Genetic Elements

Author:

Rishishwar Lavanya¹²³,Wang Lu¹²,Clayton Evan A.¹⁴,Mariño-Ramírez Leonardo²⁵,McDonald John F.¹⁴,Jordan I. King¹²³

Affiliation:

1. School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA

2. PanAmerican Bioinformatics Institute, Cali, Colombia

3. Applied Bioinformatics Laboratory, Atlanta, GA, USA

4. Ovarian Cancer Institute, Atlanta, GA, USA

5. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA

Publisher

Informa UK Limited

Subject

Genetics,Biochemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/2159256X.2017.1280116

Reference147 articles.

1. Initial sequencing and analysis of the human genome

2. Repetitive Elements May Comprise Over Two-Thirds of the Human Genome

3. A map of human genome variation from population-scale sequencing

4. An integrated map of genetic variation from 1,092 human genomes

5. A global reference for human genetic variation

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transcription termination and antitermination are critical for the fitness and function of the integrative and conjugative element Tn916;2024-09-05

2. Transposable Elements and piRNAs interaction prediction with Predictive Bi-Clustering Trees;2024-03-01

3. MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell;2024-01-11

4. DNA Transposons favour denovotranscript emergence through enrichment of transcription factor binding motifs;2023-10-03

5. Genomic object detection: An improved approach for transposable elements detection and classification using convolutional neural networks;PLOS ONE;2023-09-21

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