Harold E. Smith

4.4k total citations
61 papers, 2.4k citations indexed

About

Harold E. Smith is a scholar working on Molecular Biology, Aging and Genetics. According to data from OpenAlex, Harold E. Smith has authored 61 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 22 papers in Aging and 13 papers in Genetics. Recurrent topics in Harold E. Smith's work include Genetics, Aging, and Longevity in Model Organisms (22 papers), CRISPR and Genetic Engineering (12 papers) and Biofuel production and bioconversion (6 papers). Harold E. Smith is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (22 papers), CRISPR and Genetic Engineering (12 papers) and Biofuel production and bioconversion (6 papers). Harold E. Smith collaborates with scholars based in United States, Canada and United Kingdom. Harold E. Smith's co-authors include Aaron P. Mitchell, Samuel Ward, Steven J.M. Jones, V Reinke, Madhura Kulkarni, Stewart Scherer, Jeremy Nance, Stuart K. Kim, Rebecca Begley and John Wang and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Harold E. Smith

59 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Harold E. Smith United States 24 1.7k 786 520 299 243 61 2.4k
Asako Sugimoto Japan 30 2.6k 1.5× 1.1k 1.4× 522 1.0× 700 2.3× 848 3.5× 72 3.9k
Susan Parrish United States 10 3.6k 2.2× 901 1.1× 477 0.9× 880 2.9× 113 0.5× 13 4.5k
Ka Ming Pang United States 17 1.6k 1.0× 692 0.9× 141 0.3× 384 1.3× 405 1.7× 23 2.1k
David P. Welchman United Kingdom 9 2.2k 1.3× 1.7k 2.2× 348 0.7× 298 1.0× 576 2.4× 9 3.6k
F. Kenneth Nelson United States 16 1.2k 0.7× 307 0.4× 253 0.5× 199 0.7× 90 0.4× 22 1.9k
Marcel Tijsterman Netherlands 36 3.8k 2.3× 1.3k 1.6× 669 1.3× 804 2.7× 242 1.0× 77 4.6k
John Yochem United States 25 1.8k 1.1× 1.0k 1.3× 370 0.7× 167 0.6× 422 1.7× 36 2.6k
Igor Antoshechkin United States 29 1.8k 1.1× 404 0.5× 310 0.6× 751 2.5× 120 0.5× 50 2.9k
Andrew R. Buchman United States 20 3.0k 1.8× 498 0.6× 485 0.9× 493 1.6× 208 0.9× 23 3.6k
R. S. Edgar United States 24 2.0k 1.2× 632 0.8× 1.1k 2.1× 292 1.0× 167 0.7× 38 3.2k

Countries citing papers authored by Harold E. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Harold E. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harold E. Smith. 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 Harold E. Smith. The network helps show where Harold E. Smith may publish in the future.

Co-authorship network of co-authors of Harold E. Smith

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

All Works

20 of 20 papers shown
1.
Smith, Harold E.. (2022). Mutation Mapping and Identification by Whole-Genome Sequencing. Methods in molecular biology. 2468. 257–269. 2 indexed citations
2.
Lee, Hye‐Kyung, Ludwig Knabl, André Volland, et al.. (2021). Immune transcriptomes of highly exposed SARS-CoV-2 asymptomatic seropositive versus seronegative individuals from the Ischgl community. Scientific Reports. 11(1). 4243–4243. 13 indexed citations
3.
Schulman, David A., et al.. (2020). Identification of Suppressors oftop-2Embryonic Lethality inCaenorhabditis elegans. G3 Genes Genomes Genetics. 10(4). 1183–1191. 8 indexed citations
4.
Akella, Jyothi S., Nicole Ross, Andy Golden, et al.. (2020). Mutation of NEKL-4/NEK10 and TTLL genes suppress neuronal ciliary degeneration caused by loss of CCPP-1 deglutamylase function. PLoS Genetics. 16(10). e1009052–e1009052. 17 indexed citations
5.
Lee, Hye‐Kyung, Harold E. Smith, Chengyu Liu, Michaela Willi, & Lothar Hennighausen. (2020). Cytosine base editor 4 but not adenine base editor generates off-target mutations in mouse embryos. Communications Biology. 3(1). 19–19. 46 indexed citations
6.
Ashinsky, Beth G., Sarah E. Gullbrand, Edward D. Bonnevie, et al.. (2019). Multiscale and multimodal structure–function analysis of intervertebral disc degeneration in a rabbit model. Osteoarthritis and Cartilage. 27(12). 1860–1869. 37 indexed citations
7.
Lee, Hye‐Kyung, Michaela Willi, Harold E. Smith, et al.. (2019). Simultaneous targeting of linked loci in mouse embryos using base editing. Scientific Reports. 9(1). 1662–1662. 13 indexed citations
8.
Davison, Jack R., Sivakoteswara Rao Mandadapu, Regina Cencic, et al.. (2017). A New Natural Product Analog of Blasticidin S Reveals Cellular Uptake Facilitated by the NorA Multidrug Transporter. Antimicrobial Agents and Chemotherapy. 61(6). 10 indexed citations
9.
Lee, Hye‐Kyung, Michaela Willi, Chaochen Wang, et al.. (2017). Functional assessment of CTCF sites at cytokine-sensing mammary enhancers using CRISPR/Cas9 gene editing in mice. Nucleic Acids Research. 45(8). 4606–4618. 17 indexed citations
10.
Smith, Harold E., et al.. (2016). Mapping Challenging Mutations by Whole-Genome Sequencing. G3 Genes Genomes Genetics. 6(5). 1297–1304. 14 indexed citations
11.
Thompson, Kenneth W., et al.. (2016). The Paired-box protein PAX-3 regulates the choice between lateral and ventral epidermal cell fates in C. elegans. Developmental Biology. 412(2). 191–207. 7 indexed citations
12.
13.
Clough, Emily, Erin Jimenez, Yoo-Ah Kim, et al.. (2014). Sex- and Tissue-Specific Functions of Drosophila Doublesex Transcription Factor Target Genes. Developmental Cell. 31(6). 761–773. 99 indexed citations
14.
Smith, Harold E.. (2014). Nematode sperm motility. WormBook. 1–15. 19 indexed citations
15.
Malone, John H., Dong-Yeon Cho, Nicolas R. Mattiuzzo, et al.. (2012). Mediation of Drosophilaautosomal dosage effects and compensation by network interactions. Genome biology. 13(4). r28–r28. 77 indexed citations
16.
Kulkarni, Madhura & Harold E. Smith. (2008). E1 Ubiquitin-Activating Enzyme UBA-1 Plays Multiple Roles throughout C. elegans Development. PLoS Genetics. 4(7). e1000131–e1000131. 60 indexed citations
17.
Castillo‐Olivares, Antonio del & Harold E. Smith. (2007). Critical contact residues that mediate polymerization of nematode major sperm protein. Journal of Cellular Biochemistry. 104(2). 477–487. 5 indexed citations
18.
Reinke, V, Harold E. Smith, Jeremy Nance, et al.. (2000). A Global Profile of Germline Gene Expression in C. elegans. Molecular Cell. 6(3). 605–616. 495 indexed citations
19.
Smith, Harold E., et al.. (1993). Genetic evidence for transcriptional activation by the yeast IME1 gene product.. Genetics. 133(4). 775–784. 65 indexed citations
20.
Smith, Harold E. & Aaron P. Mitchell. (1989). A Transcriptional Cascade Governs Entry into Meiosis in Saccharomyces cerevisiae. Molecular and Cellular Biology. 9(5). 2142–2152. 45 indexed citations

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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