Nina Alperovich

2.5k total citations · 1 hit paper
15 papers, 1.5k citations indexed

About

Nina Alperovich is a scholar working on Molecular Biology, Ecology and Plant Science. According to data from OpenAlex, Nina Alperovich has authored 15 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 4 papers in Ecology and 4 papers in Plant Science. Recurrent topics in Nina Alperovich's work include CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (5 papers) and Bacteriophages and microbial interactions (4 papers). Nina Alperovich is often cited by papers focused on CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (5 papers) and Bacteriophages and microbial interactions (4 papers). Nina Alperovich collaborates with scholars based in United States and Egypt. Nina Alperovich's co-authors include John I. Glass, Hamilton O. Smith, J. Craig Venter, Nacyra Assad-Garcia, Shibu Yooseph, Matthew R. Lewis, Clyde A. Hutchison, Carole Lartigue, Prashanth P. Parmar and Rembert Pieper and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Nina Alperovich

14 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Essential genes of a minimal bacterium

2006 638 citations John I. Glass, Nacyra Assad-Garcia et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Nina Alperovich United States	9	1.1k	407	357	240	169	15	1.5k
Gwynedd A. Benders United States	8	1.3k 1.2×	435 1.1×	316 0.9×	148 0.6×	186 1.1×	9	1.6k
Chuck Merryman United States	15	1.7k 1.6×	516 1.3×	361 1.0×	147 0.6×	177 1.0×	18	2.0k
Carole Lartigue France	18	772 0.7×	285 0.7×	525 1.5×	557 2.3×	285 1.7×	42	1.4k
María Lluch‐Senar Spain	22	832 0.8×	293 0.7×	463 1.3×	400 1.7×	140 0.8×	43	1.4k
Sanjay Vashee United States	21	1.2k 1.1×	308 0.8×	282 0.8×	293 1.2×	199 1.2×	45	1.7k
Jayshree Zaveri United States	5	1.1k 1.0×	337 0.8×	180 0.5×	46 0.2×	123 0.7×	5	1.3k
Eva Yus Spain	14	827 0.8×	291 0.7×	328 0.9×	228 0.9×	99 0.6×	15	1.1k
David M. Raskin United States	9	1.2k 1.1×	985 2.4×	423 1.2×	43 0.2×	121 0.7×	20	1.6k
Kenneth M. Stedman United States	25	1.4k 1.3×	517 1.3×	1.3k 3.7×	88 0.4×	555 3.3×	53	2.2k
Marcella L. Erb United States	12	836 0.8×	321 0.8×	1.0k 2.8×	143 0.6×	246 1.5×	18	1.5k

Countries citing papers authored by Nina Alperovich

Since Specialization

Citations

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

Fields of papers citing papers by Nina Alperovich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Alperovich

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Alperovich. A scholar is included among the top collaborators of Nina Alperovich 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 Nina Alperovich. Nina Alperovich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Alperovich, Nina, et al.. (2025). Prevention of ribozyme catalysis through cDNA synthesis enables accurate RT-qPCR measurements of context-dependent ribozyme activity. RNA. 31(5). rna.080243.124–rna.080243.124.

Tonner, Peter D., Abe Pressman, Nathan D. Olson, et al.. (2023). Precision engineering of biological function with large-scale measurements and machine learning. PLoS ONE. 18(3). e0283548–e0283548. 2 indexed citations

Alperovich, Nina, Benjamin Scott, & David Ross. (2023). Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae. PLoS ONE. 18(10). e0292401–e0292401. 2 indexed citations

Alperovich, Nina, et al.. (2022). Effects of DNA template preparation on variability in cell-free protein production. PubMed. 7(1). ysac015–ysac015. 6 indexed citations

Alperovich, Nina, et al.. (2022). Best Practices for DNA Template Preparation Toward Improved Reproducibility in Cell-Free Protein Production. Methods in molecular biology. 2433. 3–50. 4 indexed citations

Rammohan, Jayan, Steven P. Lund, Nina Alperovich, et al.. (2021). Comparison of bias and resolvability in single-cell and single-transcript methods. Communications Biology. 4(1). 659–659. 4 indexed citations

Shao, Bin, Jayan Rammohan, Daniel A. Anderson, et al.. (2021). Single-cell measurement of plasmid copy number and promoter activity. Nature Communications. 12(1). 1475–1475. 56 indexed citations

Tonner, Peter D., Abe Pressman, Nathan D. Olson, et al.. (2021). The genotype‐phenotype landscape of an allosteric protein. Molecular Systems Biology. 17(3). e10179–e10179. 39 indexed citations

Oldfield, Lauren M., Alexander A. Voorhies, Nina Alperovich, et al.. (2017). Genome-wide engineering of an infectious clone of herpes simplex virus type 1 using synthetic genomics assembly methods. Proceedings of the National Academy of Sciences. 114(42). E8885–E8894. 57 indexed citations

10.

Vashee, Sanjay, Timothy B. Stockwell, Nina Alperovich, et al.. (2017). Cloning, Assembly, and Modification of the Primary Human Cytomegalovirus Isolate Toledo by Yeast-Based Transformation-Associated Recombination. mSphere. 2(5). 36 indexed citations

11.

Krishnakumar, R., Daniel H. Haft, Jayshree Zaveri, et al.. (2014). Simultaneous non-contiguous deletions using large synthetic DNA and site-specific recombinases. Nucleic Acids Research. 42(14). e111–e111. 19 indexed citations

12.

Benders, Gwynedd A., Vladimir N. Noskov, Carole Lartigue, et al.. (2010). Cloning whole bacterial genomes in yeast. Nucleic Acids Research. 38(8). 2558–2569. 105 indexed citations

13.

Lartigue, Carole, Sanjay Vashee, Mikkel A. Algire, et al.. (2009). Creating Bacterial Strains from Genomes That Have Been Cloned and Engineered in Yeast. Science. 325(5948). 1693–1696. 208 indexed citations

14.

Lartigue, Carole, John I. Glass, Nina Alperovich, et al.. (2007). Genome Transplantation in Bacteria: Changing One Species to Another. Science. 317(5838). 632–638. 288 indexed citations

15.

Glass, John I., Nacyra Assad-Garcia, Nina Alperovich, et al.. (2006). Essential genes of a minimal bacterium. Proceedings of the National Academy of Sciences. 103(2). 425–430. 638 indexed citations breakdown →

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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