Emma W Vaimberg

6.3k citations
6 papers · 3.4k indexed · 2 hit papers · h-index 6
Topics
CRISPR and Genetic Engineering (4 papers)RNA and protein synthesis mechanisms (3 papers)Gene Regulatory Network Analysis (2 papers)
Partner nations
United StatesChina

In The Last Decade

Emma W Vaimberg

6 papers receiving 3.4k citations

Hit Papers

Optimized sgRNA design to maximize activity and minimize ...20162026201920222016201850010001.5k2.0k2.5k

Peers

Emma W Vaimberg
Comparison fields: 5 of 99
  • Molecular Biology 2.9k
  • Genetics 468
  • Oncology 395
  • Immunology 295
  • Plant Science 256
Replace Meagan E. Sullender with:
Meagan E. Sullender United States
Han Xu United States
Mudra Hegde United States
Jacqueline E. Villalta United States
Shondra M. Pruett‐Miller United States
James K. Nuñez United States
Xi Shi China
Jeongbin Park South Korea
Jeffrey A. Hussmann United States
Emma W Vaimberg relative to Meagan E. Sullender United States Meagan E. Sullender's profile →
Citations per field
00.5×1.5×
Meagan E. Sullender · 1×
Citations per year

Countries citing papers authored by Emma W Vaimberg

Since Specialization
Citations

This map shows the geographic impact of Emma W Vaimberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emma W Vaimberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma W Vaimberg more than expected).

Fields of papers citing papers by Emma W Vaimberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emma W Vaimberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emma W Vaimberg. The network helps show where Emma W Vaimberg may publish in the future.

Co-authorship network of co-authors of Emma W Vaimberg

This figure shows the co-authorship network connecting the top 25 collaborators of Emma W Vaimberg. A scholar is included among the top collaborators of Emma W Vaimberg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emma W Vaimberg. Emma W Vaimberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1 9
2 8
3
Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalitiesbreakdown →
505
4 39
5 182
6
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9breakdown →
2646

About Emma W Vaimberg

Emma W Vaimberg is a scholar working on Aging, Safety Research and Molecular Biology, having authored 6 papers that have together received 3.4k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), RNA and protein synthesis mechanisms (3 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Aging (169 citations), Business and International Management (133 citations) and Molecular Biology (2.9k citations). Emma W Vaimberg has collaborated with scholars based in United States and China. Frequent co-authors include David E. Root, John G. Doench, Mudra Hegde, Meagan E. Sullender, Katherine Donovan, Nicolò Fusi, Jennifer Listgarten, Robert C. Orchard, Craig B. Wilen and Zuzana Tóthová. Their work appears in journals such as Nature Communications, Nature Biotechnology and PLoS ONE.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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