Daniel J. Wiegand

1.9k total citations · 1 hit paper
6 papers, 1.4k citations indexed

About

Daniel J. Wiegand is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, Daniel J. Wiegand has authored 6 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Ecology and 2 papers in Genetics. Recurrent topics in Daniel J. Wiegand's work include RNA and protein synthesis mechanisms (4 papers), CRISPR and Genetic Engineering (2 papers) and Bacteriophages and microbial interactions (2 papers). Daniel J. Wiegand is often cited by papers focused on RNA and protein synthesis mechanisms (4 papers), CRISPR and Genetic Engineering (2 papers) and Bacteriophages and microbial interactions (2 papers). Daniel J. Wiegand collaborates with scholars based in United States, Switzerland and South Korea. Daniel J. Wiegand's co-authors include George M. Church, Alejandro Chavez, Samira Kiani, Benjamin W. Pruitt, Christopher D. Guzman, Noah Davidsohn, John Aach, Marcelle Tuttle, Benjamin E. Housden and Norbert Perrimon and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Nature Methods.

In The Last Decade

Daniel J. Wiegand

6 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.

Highly efficient Cas9-mediated transcriptional programming

2015 1.2k citations Alejandro Chavez, Jonathan Scheiman et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel J. Wiegand United States	6	1.3k	204	122	89	74	6	1.4k
Samantha J Linder United States	6	1.5k 1.1×	301 1.5×	112 0.9×	126 1.4×	97 1.3×	6	1.5k
Ravi Alla United States	5	1.1k 0.9×	240 1.2×	91 0.7×	94 1.1×	93 1.3×	8	1.2k
Antonia A. Dominguez United States	12	1.3k 1.0×	259 1.3×	83 0.7×	118 1.3×	110 1.5×	16	1.5k
Xiaohui Zhang China	10	1.1k 0.8×	333 1.6×	88 0.7×	144 1.6×	112 1.5×	24	1.3k
Benjamin W. Pruitt United States	8	2.0k 1.5×	295 1.4×	179 1.5×	140 1.6×	122 1.6×	9	2.1k
Robert J. Ihry United States	7	847 0.7×	237 1.2×	65 0.5×	50 0.6×	69 0.9×	9	1.1k
Qunshan Huang China	5	880 0.7×	256 1.3×	75 0.6×	117 1.3×	95 1.3×	7	989
Quan Ho United States	6	1.4k 1.1×	266 1.3×	105 0.9×	104 1.2×	89 1.2×	6	1.6k
Suhani Vora United States	5	1.6k 1.3×	247 1.2×	155 1.3×	113 1.3×	110 1.5×	6	1.7k
Martin Del Castillo Velasco‐Herrera United Kingdom	9	925 0.7×	161 0.8×	63 0.5×	42 0.5×	61 0.8×	14	1.1k

Countries citing papers authored by Daniel J. Wiegand

Since Specialization

Citations

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

Fields of papers citing papers by Daniel J. Wiegand

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Wiegand. 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 Daniel J. Wiegand. The network helps show where Daniel J. Wiegand may publish in the future.

Co-authorship network of co-authors of Daniel J. Wiegand

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

All Works

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6 of 6 papers shown

1.

Wiegand, Daniel J., Jonathan Rittichier, Howon Lee, et al.. (2024). Template-independent enzymatic synthesis of RNA oligonucleotides. Nature Biotechnology. 43(5). 762–772. 17 indexed citations

2.

Lee, Howon, Daniel J. Wiegand, Sukanya Punthambaker, et al.. (2020). Photon-directed multiplexed enzymatic DNA synthesis for molecular digital data storage. Nature Communications. 11(1). 5246–5246. 77 indexed citations

3.

Kuru, Erkin, et al.. (2020). Release Factor Inhibiting Antimicrobial Peptides Improve Nonstandard Amino Acid Incorporation in Wild-type Bacterial Cells. ACS Chemical Biology. 15(7). 1852–1861. 18 indexed citations

4.

Wiegand, Daniel J., Henry H. Lee, Nili Ostrov, & George M. Church. (2019). Cell-free Protein Expression Using the Rapidly Growing Bacterium <em>Vibrio natriegens</em>. Journal of Visualized Experiments. 17 indexed citations

5.

Wiegand, Daniel J., Henry H. Lee, Nili Ostrov, & George M. Church. (2018). Establishing a Cell-Free Vibrio natriegens Expression System. ACS Synthetic Biology. 7(10). 2475–2479. 64 indexed citations

6.

Chavez, Alejandro, Jonathan Scheiman, Suhani Vora, et al.. (2015). Highly efficient Cas9-mediated transcriptional programming. Nature Methods. 12(4). 326–328. 1183 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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