D-Index & Metrics Best Publications
Research.com 2022 Best Scientist Award Badge
Genetics
China
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Best Scientists D-index 179 Citations 252,200 1,352 World Ranking 432 National Ranking 8
Genetics D-index 159 Citations 205,155 1,057 World Ranking 57 National Ranking 2

Research.com Recognitions

Awards & Achievements

2023 - Research.com Genetics in China Leader Award

2022 - Research.com Best Scientist Award

2022 - Research.com Genetics and Molecular Biology in China Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Internal medicine
  • Genetics

Genetics, CRISPR, Cas9, Computational biology and Gene are his primary areas of study. Genome editing, Genome, Guide RNA, RNA and Genome engineering are among the areas of Genetics where Feng Zhang concentrates his study. Within one scientific family, Feng Zhang focuses on topics pertaining to Gene targeting under Genome editing, and may sometimes address concerns connected to Point mutation.

His study in the field of CRISPR interference and Trans-activating crRNA is also linked to topics like Complex formation. In his research on the topic of Cas9, Gene knockout is strongly related with Gene Knockout Techniques. His study in Computational biology is interdisciplinary in nature, drawing from both Bioinformatics, DNA, Regulation of gene expression, Transcription and Effector.

His most cited work include:

  • Multiplex Genome Engineering Using CRISPR/Cas Systems (9543 citations)
  • Genome engineering using the CRISPR-Cas9 system (5805 citations)
  • Development and applications of CRISPR-Cas9 for genome engineering. (3335 citations)

What are the main themes of his work throughout his whole career to date?

Feng Zhang focuses on Genetics, CRISPR, Computational biology, Gene and Internal medicine. His study in Genome, Genome-wide association study, Single-nucleotide polymorphism, Copy-number variation and Locus falls under the purview of Genetics. His research in Genome-wide association study intersects with topics in Genetic association and Candidate gene.

Cas9, Genome editing, Guide RNA, Genome engineering and Trans-activating crRNA are the subjects of his CRISPR studies. His Computational biology research is multidisciplinary, incorporating elements of RNA, DNA and Effector. His studies in Internal medicine integrate themes in fields like Endocrinology and Cardiology.

He most often published in these fields:

  • Genetics (33.05%)
  • CRISPR (20.16%)
  • Computational biology (20.35%)

What were the highlights of his more recent work (between 2019-2021)?

  • Gene (19.57%)
  • Computational biology (20.35%)
  • Genetics (33.05%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Gene, Computational biology, Genetics, Internal medicine and CRISPR. His Gene study often links to related topics such as Autism spectrum disorder. His Computational biology study incorporates themes from Genome and Genome-wide association study.

The study incorporates disciplines such as Gastroenterology, Endocrinology and Cardiology in addition to Internal medicine. Feng Zhang is studying Genome editing, which is a component of CRISPR. His Genome editing study frequently links to other fields, such as Cas9.

Between 2019 and 2021, his most popular works were:

  • Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. (394 citations)
  • Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants. (282 citations)
  • Point-of-care testing for COVID-19 using SHERLOCK diagnostics (98 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Multiplex Genome Engineering Using CRISPR/Cas Systems

Le Cong;Le Cong;F. Ann Ran;F. Ann Ran;David M. Cox;David M. Cox;Shuailiang Lin;Shuailiang Lin.
Science (2013)

21645 Citations

Genome engineering using the CRISPR-Cas9 system

F Ann Ran;Patrick D Hsu;Jason Wright;Vineeta Agarwala;Vineeta Agarwala.
Nature Protocols (2013)

15977 Citations

Development and applications of CRISPR-Cas9 for genome engineering.

Patrick D. Hsu;Patrick D. Hsu;Patrick D. Hsu;Eric S. Lander;Feng Zhang;Feng Zhang.
Cell (2014)

14511 Citations

Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells

Ophir Shalem;Ophir Shalem;Neville E Sanjana;Neville E Sanjana;Ella Hartenian;Xi-Shun Shi.
Science (2014)

11951 Citations

Millisecond-timescale, genetically targeted optical control of neural activity.

Edward S Boyden;Feng Zhang;Ernst Bamberg;Georg Nagel.
Nature Neuroscience (2005)

5016 Citations

DNA targeting specificity of RNA-guided Cas9 nucleases

Patrick D Hsu;David Arthur Scott;David Arthur Scott;Joshua A Weinstein;Joshua A Weinstein;F. Ann Ran;F. Ann Ran;F. Ann Ran.
Nature Biotechnology (2013)

4444 Citations

One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering.

Haoyi Wang;Hui Yang;Chikdu S. Shivalila;Meelad M. Dawlaty.
Cell (2013)

3775 Citations

Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity

F. Ann Ran;Patrick D. Hsu;Chie Yu Lin;Jonathan S. Gootenberg.
Cell (2013)

3558 Citations

Improved vectors and genome-wide libraries for CRISPR screening.

Neville E Sanjana;Ophir Shalem;Feng Zhang.
Nature Methods (2014)

3500 Citations

Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system.

Bernd Zetsche;Jonathan S. Gootenberg;Omar O. Abudayyeh;Ian M. Slaymaker.
Cell (2015)

3438 Citations

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