Daniel A. Nissley

767 total citations
23 papers, 459 citations indexed

About

Daniel A. Nissley is a scholar working on Molecular Biology, Infectious Diseases and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Daniel A. Nissley has authored 23 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 5 papers in Infectious Diseases and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Daniel A. Nissley's work include RNA and protein synthesis mechanisms (11 papers), Protein Structure and Dynamics (10 papers) and SARS-CoV-2 and COVID-19 Research (5 papers). Daniel A. Nissley is often cited by papers focused on RNA and protein synthesis mechanisms (11 papers), Protein Structure and Dynamics (10 papers) and SARS-CoV-2 and COVID-19 Research (5 papers). Daniel A. Nissley collaborates with scholars based in United States, United Kingdom and Vietnam. Daniel A. Nissley's co-authors include Edward P. O’Brien, Mai Suan Li, Charlotte M. Deane, Carlos Outeiral, Hoang Linh Nguyen, Nguyen Quoc Thai, Fabio Trovato, Yang Jiang, Nabeel Ahmed and Hung Van Nguyen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.

In The Last Decade

Daniel A. Nissley

22 papers receiving 453 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel A. Nissley United States 12 345 125 69 62 52 23 459
Suvrajit Maji United States 9 254 0.7× 165 1.3× 40 0.6× 47 0.8× 47 0.9× 14 466
Jorgen Nelson United States 5 401 1.2× 28 0.2× 77 1.1× 104 1.7× 36 0.7× 5 501
Lalit Deshmukh United States 13 358 1.0× 109 0.9× 61 0.9× 32 0.5× 33 0.6× 30 489
Santrupti Nerli United States 12 331 1.0× 55 0.4× 78 1.1× 44 0.7× 21 0.4× 13 423
José Xavier Neto Brazil 15 258 0.7× 55 0.4× 27 0.4× 31 0.5× 17 0.3× 34 458
M. Geralt United States 12 313 0.9× 97 0.8× 74 1.1× 11 0.2× 24 0.5× 24 426
Akash Bhattacharya United States 13 521 1.5× 216 1.7× 80 1.2× 14 0.2× 48 0.9× 35 809
Matthew Tien United States 4 314 0.9× 19 0.2× 64 0.9× 28 0.5× 16 0.3× 5 395
Xiaoyin Cai China 13 255 0.7× 64 0.5× 31 0.4× 35 0.6× 100 1.9× 31 496
Ieva Drulyte Netherlands 7 159 0.5× 79 0.6× 33 0.5× 23 0.4× 23 0.4× 14 292

Countries citing papers authored by Daniel A. Nissley

Since Specialization
Citations

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

Fields of papers citing papers by Daniel A. Nissley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel A. Nissley

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel A. Nissley. A scholar is included among the top collaborators of Daniel A. Nissley 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 A. Nissley. Daniel A. Nissley 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.
Nissley, Daniel A., Daniel B. Wilson, Mikhail A. Kutuzov, et al.. (2025). The molecular reach of antibodies crucially underpins their viral neutralisation capacity. Nature Communications. 16(1). 338–338. 2 indexed citations
2.
Dreyer, Frédéric A., Constantin Schneider, Aleksandr Kovaltsuk, et al.. (2025). Computational design of therapeutic antibodies with improved developability: efficient traversal of binder landscapes and rescue of escape mutations. mAbs. 17(1). 2511220–2511220. 1 indexed citations
3.
Nissley, Daniel A., et al.. (2024). Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2. The Journal of Chemical Physics. 160(5). 3 indexed citations
4.
Nissley, Daniel A., et al.. (2024). Synonymous Mutations Can Alter Protein Dimerization Through Localized Interface Misfolding Involving Self-entanglements. Journal of Molecular Biology. 436(6). 168487–168487. 3 indexed citations
5.
Dreyer, Frédéric A., et al.. (2024). ABodyBuilder3: improved and scalable antibody structure predictions. Bioinformatics. 40(10). 15 indexed citations
6.
Nissley, Daniel A., et al.. (2023). Is Posttranslational Folding More Efficient Than Refolding from a Denatured State: A Computational Study. The Journal of Physical Chemistry B. 127(21). 4761–4774. 1 indexed citations
7.
Raybould, Matthew I. J., Daniel A. Nissley, Sandeep Kumar, & Charlotte M. Deane. (2023). Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies. Frontiers in Immunology. 13. 1080596–1080596. 7 indexed citations
8.
Nissley, Daniel A., et al.. (2023). How soluble misfolded proteins bypass chaperones at the molecular level. Nature Communications. 14(1). 3689–3689. 10 indexed citations
9.
Nissley, Daniel A., et al.. (2022). Universal protein misfolding intermediates can bypass the proteostasis network and remain soluble and less functional. Nature Communications. 13(1). 30 indexed citations
10.
Nguyen, Hung Van, et al.. (2022). Cocktail of REGN Antibodies Binds More Strongly to SARS-CoV-2 Than Its Components, but the Omicron Variant Reduces Its Neutralizing Ability. The Journal of Physical Chemistry B. 126(15). 2812–2823. 14 indexed citations
11.
Nissley, Daniel A., et al.. (2021). Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains. Bioinformatics. 37(13). 1853–1859. 3 indexed citations
12.
Nguyen, Hung Van, et al.. (2021). Electrostatic Interactions Explain the Higher Binding Affinity of the CR3022 Antibody for SARS-CoV-2 than the 4A8 Antibody. The Journal of Physical Chemistry B. 125(27). 7368–7379. 21 indexed citations
13.
Nguyen, Hoang Linh, et al.. (2020). Does SARS-CoV-2 Bind to Human ACE2 More Strongly Than Does SARS-CoV?. The Journal of Physical Chemistry B. 124(34). 7336–7347. 101 indexed citations
14.
Trovato, Fabio, et al.. (2019). Domain topology, stability, and translation speed determine mechanical force generation on the ribosome. Proceedings of the National Academy of Sciences. 116(12). 5523–5532. 36 indexed citations
15.
Kosolapov, Andrey, Phillip S. Hudson, Daniel A. Nissley, et al.. (2018). Origins of the Mechanochemical Coupling of Peptide Bond Formation to Protein Synthesis. Journal of the American Chemical Society. 140(15). 5077–5087. 31 indexed citations
16.
Nissley, Daniel A. & Edward P. O’Brien. (2018). Structural Origins of FRET-Observed Nascent Chain Compaction on the Ribosome. The Journal of Physical Chemistry B. 122(43). 9927–9937. 16 indexed citations
17.
18.
Nissley, Daniel A., Ajeet K. Sharma, Nabeel Ahmed, et al.. (2016). Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding. Nature Communications. 7(1). 10341–10341. 36 indexed citations
19.
Nissley, Daniel A. & Edward P. O’Brien. (2016). Altered Co-Translational Processing Plays a Role in Huntington's Pathogenesis—A Hypothesis. Frontiers in Molecular Neuroscience. 9. 54–54. 4 indexed citations
20.
Nissley, Daniel A. & Edward P. O’Brien. (2014). Timing Is Everything: Unifying Codon Translation Rates and Nascent Proteome Behavior. Journal of the American Chemical Society. 136(52). 17892–17898. 38 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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