Stan Letovsky

2.9k total citations
11 papers, 872 citations indexed

About

Stan Letovsky is a scholar working on Molecular Biology, Infectious Diseases and Computer Networks and Communications. According to data from OpenAlex, Stan Letovsky has authored 11 papers receiving a total of 872 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Infectious Diseases and 1 paper in Computer Networks and Communications. Recurrent topics in Stan Letovsky's work include RNA and protein synthesis mechanisms (3 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Stan Letovsky is often cited by papers focused on RNA and protein synthesis mechanisms (3 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Stan Letovsky collaborates with scholars based in United States, Singapore and Israel. Stan Letovsky's co-authors include Doron Lipson, Simon Kasif, Yu Zheng, Chunming Ding, Charles R. Cantor, Ulaş Karaöz, T. M. Murali, Shyamala Maheswaran, Suchismita Paul and Gianmarco Contino and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Biotechnology.

In The Last Decade

Stan Letovsky

9 papers receiving 837 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stan Letovsky United States	7	786	168	133	88	75	11	872
Quan Xu China	10	858 1.1×	230 1.4×	52 0.4×	146 1.7×	53 0.7×	13	1.0k
Maria Keays United Kingdom	5	457 0.6×	77 0.5×	82 0.6×	65 0.7×	37 0.5×	5	617
Andrew Tikhonov United Kingdom	4	519 0.7×	62 0.4×	94 0.7×	62 0.7×	41 0.5×	5	686
Jung Eun Shim South Korea	14	887 1.1×	133 0.8×	138 1.0×	205 2.3×	76 1.0×	24	1.1k
Hsien-Da Huang Taiwan	7	642 0.8×	72 0.4×	254 1.9×	60 0.7×	33 0.4×	8	737
Yuming Zhao China	18	725 0.9×	118 0.7×	130 1.0×	23 0.3×	110 1.5×	48	852
Giovanni Stracquadanio United Kingdom	11	722 0.9×	88 0.5×	56 0.4×	152 1.7×	37 0.5×	36	888
E Schmidt Germany	13	760 1.0×	144 0.9×	73 0.5×	131 1.5×	109 1.5×	43	1.0k
Hongyu Zhao China	13	499 0.6×	103 0.6×	96 0.7×	78 0.9×	37 0.5×	42	764
Shijia Zhu United States	11	791 1.0×	83 0.5×	82 0.6×	105 1.2×	18 0.2×	28	987

Countries citing papers authored by Stan Letovsky

Since Specialization

Citations

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

Fields of papers citing papers by Stan Letovsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stan Letovsky

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Alfego, David, et al.. (2023). Antibody titer levels and the effect on subsequent SARS-CoV-2 infection in a large US-based cohort. Heliyon. 9(2). e13103–e13103. 5 indexed citations

2.

Alfego, David, et al.. (2021). Follow-Up SARS-CoV-2 PCR Testing Outcomes From a Large Reference Lab in the US. Frontiers in Public Health. 9. 679012–679012. 1 indexed citations

3.

Raz, Tal, Philipp Kapranov, Doron Lipson, et al.. (2011). Protocol Dependence of Sequencing-Based Gene Expression Measurements. PLoS ONE. 6(5). e19287–e19287. 70 indexed citations

4.

Raz, Tal, Daniel Jones, Stan Letovsky, et al.. (2011). RNA Sequencing and Quantitation Using the Helicos Genetic Analysis System. Methods in molecular biology. 733. 37–49. 8 indexed citations

5.

Ting, David T., Doron Lipson, Suchismita Paul, et al.. (2011). Aberrant Overexpression of Satellite Repeats in Pancreatic and Other Epithelial Cancers. Science. 331(6017). 593–596. 393 indexed citations

6.

Giladi, Eldar, John Healy, Gene Myers, et al.. (2010). Error Tolerant Indexing and Alignment of Short Reads with Covering Template Families. Journal of Computational Biology. 17(10). 1397–1411. 18 indexed citations

7.

Lipson, Doron, Tal Raz, Daniel Jones, et al.. (2009). Quantification of the yeast transcriptome by single-molecule sequencing. Nature Biotechnology. 27(7). 652–658. 141 indexed citations

8.

Letovsky, Stan, et al.. (2009). Biological Process Linkage Networks. PLoS ONE. 4(4). e5313–e5313. 26 indexed citations

9.

Karaöz, Ulaş, T. M. Murali, Stan Letovsky, et al.. (2004). Whole-genome annotation by using evidence integration in functional-linkage networks. Proceedings of the National Academy of Sciences. 101(9). 2888–2893. 209 indexed citations

10.

Letovsky, Stan. (1997). The bioWidget consortium. Trends in Genetics. 13(11). 461–461. 1 indexed citations

11.

Letovsky, Stan, et al.. (1990). Panel: scientific data management for human genome applications. 13(3). 51.

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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