Next-generation transcriptome assembly

Clicks: 243
ID: 111923
2011
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Advances in sequencing technologies, assembly algorithms and computing power are making it feasible to assemble the entire transcriptome from short RNA reads. The article reviews the transcriptome assembly strategies, their advantages and limitations and how to apply them effectively.
Reference Key
martin2011naturenext-generation Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jeffrey A. Martin;Zhong Wang;Jeffrey A. Martin;Zhong Wang;
Journal Nature Reviews Genetics
Year 2011
DOI
doi:10.1038/nrg3068
URL
https://doi.org/10.1038%2Fnrg3068
Keywords
Technology gene expression next-generation sequencing rna transcriptomics rna sequencing National Center for Biotechnology Information NCBI NLM MEDLINE Molecular review animals humans pubmed abstract nih national institutes of health national library of medicine models research support u.s. gov't non-p.h.s. Sequence Analysis Base Sequence Molecular Sequence Data gene expression profiling / methods gene library biological cloning dna / methods pmid:21897427 doi:10.1038/nrg3068 jeffrey a martin zhong wang gene expression profiling / trends* molecular sequence annotation / methods molecular sequence annotation / trends dna / trends rna / methods rna / trends

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.