Sergey Shmakov

30 papers receiving 5.2k citations

Hit Papers

Diversity and evolution of class 2 CRISPR–Cas systems 2017 · 761 citations
761201520262018202250010001.5k

Peers

Sergey Shmakov
Comparison fields: 5 of 102
  • Business and International Management 607
  • Aging 216
  • Molecular Biology 4.9k
  • Endocrinology 279
  • Insect Science 662
Replace Ekaterina Semenova with:
Ekaterina Semenova United States
Lucas B. Harrington United States
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Citations per field
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Citations per year

Countries citing papers authored by Sergey Shmakov

Since Specialization
Citations

This map shows the geographic impact of Sergey Shmakov'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 Sergey Shmakov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Shmakov more than expected).

Fields of papers citing papers by Sergey Shmakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergey Shmakov. 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 Sergey Shmakov. The network helps show where Sergey Shmakov may publish in the future.

Co-authors

The 25 scholars most cited alongside Sergey Shmakov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sergey Shmakov Line = papers co-authored together Sergey Shmakov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector
Hit paper breakdown →
20161689
2
Discovery and Functional Characterization of Diverse Class 2 CRISPR-Cas Systems
Hit paper breakdown →
2015919
3
Diversity and evolution of class 2 CRISPR–Cas systems
Hit paper breakdown →
2017761
4
Cas13b Is a Type VI-B CRISPR-Associated RNA-Guided RNase Differentially Regulated by Accessory Proteins Csx27 and Csx28
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2017434
5 2017186
6 2019180
7 2017157
8 2021118
9 2018104
10 202173
11 202066
12 201456
13 201755
14 202053
15 201746
16 201645
17 202337
18 201636
19 201833
20 201630

About Sergey Shmakov

Sergey Shmakov is a scholar working on Insect Science, Aging, Molecular Biology, Endocrinology and Genetics, having authored 30 papers that have together received 5.3k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (28 papers), RNA and protein synthesis mechanisms (12 papers), Insect symbiosis and bacterial influences (10 papers), Advanced biosensing and bioanalysis techniques (6 papers), Plant Virus Research Studies (6 papers), Bacterial Genetics and Biotechnology (5 papers), Bacteriophages and microbial interactions (5 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Business and International Management (607 citations), Aging (216 citations), Molecular Biology (4.9k citations), Endocrinology (279 citations) and Insect Science (662 citations). Sergey Shmakov has collaborated with scholars based in United States, Russia and United Kingdom. Frequent co-authors include Eugene V. Koonin, Kira S. Makarova, Konstantin Severinov, Feng Zhang, Jonathan S. Gootenberg, Omar O. Abudayyeh, Yuri I. Wolf, David Cox, Ekaterina Semenova and Silvana Konermann. Their work appears in journals such as Nucleic Acids Research, The CRISPR Journal, Proceedings of the National Academy of Sciences, Molecular Cell and Nature Reviews Microbiology.

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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