Literature DB >> 30202870

SequencEnG: an interactive knowledge base of sequencing techniques.

Yi Zhang1,2, Mohith Manjunath2, Yeonsung Kim2, Joerg Heintz2, Jun S Song2,3.   

Abstract

SUMMARY: Next-generation sequencing (NGS) techniques are revolutionizing biomedical research by providing powerful methods for generating genomic and epigenomic profiles. The rapid progress is posing an acute challenge to students and researchers to stay acquainted with the numerous available methods. We have developed an interactive online educational resource called Sequencing Techniques Engine for Genomics (SequencEnG) to provide a tree-structured knowledge base of 66 different sequencing techniques and step-by-step NGS data analysis pipelines comparing popular tools. SequencEnG is designed to facilitate barrier-free learning of current NGS techniques and provides a user-friendly interface for searching through experimental and analysis methods.
AVAILABILITY AND IMPLEMENTATION: SequencEnG is part of the project Knowledge Engine for Genomics (KnowEnG) and is freely available at http://education.knoweng.org/sequenceng/.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mesh:

Year:  2019        PMID: 30202870      PMCID: PMC6478014          DOI: 10.1093/bioinformatics/bty794

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

1.  Differential analysis of RNA-seq incorporating quantification uncertainty.

Authors:  Harold Pimentel; Nicolas L Bray; Suzette Puente; Páll Melsted; Lior Pachter
Journal:  Nat Methods       Date:  2017-06-05       Impact factor: 28.547

2.  Near-optimal probabilistic RNA-seq quantification.

Authors:  Nicolas L Bray; Harold Pimentel; Páll Melsted; Lior Pachter
Journal:  Nat Biotechnol       Date:  2016-04-04       Impact factor: 54.908

Review 3.  DNA sequencing at 40: past, present and future.

Authors:  Jay Shendure; Shankar Balasubramanian; George M Church; Walter Gilbert; Jane Rogers; Jeffery A Schloss; Robert H Waterston
Journal:  Nature       Date:  2017-10-11       Impact factor: 49.962

4.  Toward a Shared Vision for Cancer Genomic Data.

Authors:  Robert L Grossman; Allison P Heath; Vincent Ferretti; Harold E Varmus; Douglas R Lowy; Warren A Kibbe; Louis M Staudt
Journal:  N Engl J Med       Date:  2016-09-22       Impact factor: 91.245

5.  TeachEnG: a Teaching Engine for Genomics.

Authors:  Minji Kim; Yeonsung Kim; Lei Qian; Jun S Song
Journal:  Bioinformatics       Date:  2017-10-15       Impact factor: 6.937

6.  Cistrome: an integrative platform for transcriptional regulation studies.

Authors:  Tao Liu; Jorge A Ortiz; Len Taing; Clifford A Meyer; Bernett Lee; Yong Zhang; Hyunjin Shin; Swee S Wong; Jian Ma; Ying Lei; Utz J Pape; Michael Poidinger; Yiwen Chen; Kevin Yeung; Myles Brown; Yaron Turpaz; X Shirley Liu
Journal:  Genome Biol       Date:  2011-08-22       Impact factor: 13.583

7.  OMICtools: an informative directory for multi-omic data analysis.

Authors:  Vincent J Henry; Anita E Bandrowski; Anne-Sophie Pepin; Bruno J Gonzalez; Arnaud Desfeux
Journal:  Database (Oxford)       Date:  2014-07-14       Impact factor: 3.451

8.  Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level.

Authors:  B Ian Hutchins; Xin Yuan; James M Anderson; George M Santangelo
Journal:  PLoS Biol       Date:  2016-09-06       Impact factor: 8.029

9.  Comparison of computational methods for Hi-C data analysis.

Authors:  Francesco Ferrari; Silvio Bicciato; Mattia Forcato; Chiara Nicoletti; Koustav Pal; Carmen Maria Livi
Journal:  Nat Methods       Date:  2017-06-12       Impact factor: 28.547

10.  An integrated encyclopedia of DNA elements in the human genome.

Authors: 
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

View more
  2 in total

Review 1.  Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis.

Authors:  Carol Chase Huizar; Itay Raphael; Thomas G Forsthuber
Journal:  Cell Immunol       Date:  2020-09-20       Impact factor: 4.868

2.  Deep learning for cancer type classification and driver gene identification.

Authors:  Zexian Zeng; Chengsheng Mao; Andy Vo; Xiaoyu Li; Janna Ore Nugent; Seema A Khan; Susan E Clare; Yuan Luo
Journal:  BMC Bioinformatics       Date:  2021-10-25       Impact factor: 3.169

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.