Matthew J. Grisewood

579 total citations
9 papers, 392 citations indexed

About

Matthew J. Grisewood is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Mechanics of Materials. According to data from OpenAlex, Matthew J. Grisewood has authored 9 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Mechanics of Materials. Recurrent topics in Matthew J. Grisewood's work include Protein Structure and Dynamics (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Enzyme Catalysis and Immobilization (2 papers). Matthew J. Grisewood is often cited by papers focused on Protein Structure and Dynamics (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Enzyme Catalysis and Immobilization (2 papers). Matthew J. Grisewood collaborates with scholars based in United States. Matthew J. Grisewood's co-authors include Costas D. Maranas, Robert J. Pantazes, Brian F. Pfleger, Richard A. Friesner, Steven V. Jerome, Edward B. Miller, Dan Sindhikara, Steven L. Dixon, Ratul Chowdhury and Dawn M. Troast and has published in prestigious journals such as Nature Communications, PLoS ONE and ACS Catalysis.

In The Last Decade

Matthew J. Grisewood

9 papers receiving 387 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew J. Grisewood United States	8	304	84	67	53	32	9	392
Ming‐Shen Lin Taiwan	10	211 0.7×	64 0.8×	73 1.1×	37 0.7×	16 0.5×	11	391
Jens Rudat Germany	12	417 1.4×	51 0.6×	107 1.6×	15 0.3×	96 3.0×	34	520
Xian Jin China	10	236 0.8×	13 0.2×	39 0.6×	68 1.3×	92 2.9×	15	372
Carlton P. Jones United States	10	149 0.5×	73 0.9×	73 1.1×	37 0.7×	6 0.2×	15	401
Rosalie Lipsh‐Sokolik Israel	9	405 1.3×	52 0.6×	96 1.4×	16 0.3×	35 1.1×	12	501
Junyi Li China	12	99 0.3×	125 1.5×	119 1.8×	12 0.2×	13 0.4×	17	499
Stefan Leitgeb Austria	13	308 1.0×	114 1.4×	77 1.1×	5 0.1×	19 0.6×	20	429
Ajoy Velayudhan United States	14	435 1.4×	253 3.0×	34 0.5×	14 0.3×	16 0.5×	47	691
Mario Pink Germany	12	198 0.7×	43 0.5×	43 0.6×	15 0.3×	22 0.7×	29	477
Sean M. Law United States	11	291 1.0×	54 0.6×	73 1.1×	58 1.1×	24 0.8×	16	414

Countries citing papers authored by Matthew J. Grisewood

Since Specialization

Citations

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

Fields of papers citing papers by Matthew J. Grisewood

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew J. Grisewood

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

All Works

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9 of 9 papers shown

Miller, Edward B., Robert B. Murphy, Dan Sindhikara, et al.. (2021). Reliable and Accurate Solution to the Induced Fit Docking Problem for Protein–Ligand Binding. Journal of Chemical Theory and Computation. 17(4). 2630–2639. 104 indexed citations

Chowdhury, Ratul, et al.. (2020). IPRO+/−: Computational Protein Design Tool Allowing for Insertions and Deletions. Structure. 28(12). 1344–1357.e4. 9 indexed citations

Chowdhury, Ratul, Tingwei Ren, Manish Shankla, et al.. (2018). PoreDesigner for tuning solute selectivity in a robust and highly permeable outer membrane pore. Nature Communications. 9(1). 3661–3661. 55 indexed citations

Grisewood, Matthew J., James G. Ferry, & Costas D. Maranas. (2018). Computationally Exploring and Alleviating the Kinetic Bottlenecks of Anaerobic Methane Oxidation. Frontiers in Environmental Science. 6. 2 indexed citations

Grisewood, Matthew J., Néstor J. Hernández Lozada, James B. Thoden, et al.. (2017). Computational Redesign of Acyl-ACP Thioesterase with Improved Selectivity toward Medium-Chain-Length Fatty Acids. ACS Catalysis. 7(6). 3837–3849. 76 indexed citations

Mueller, Thomas J. J., Matthew J. Grisewood, Hadi Nazem‐Bokaee, et al.. (2014). Methane oxidation by anaerobic archaea for conversion to liquid fuels. Journal of Industrial Microbiology & Biotechnology. 42(3). 391–401. 23 indexed citations

Pantazes, Robert J., et al.. (2014). The Iterative Protein Redesign and Optimization (IPRO) suite of programs. Journal of Computational Chemistry. 36(4). 251–263. 33 indexed citations

Grisewood, Matthew J., et al.. (2013). OptZyme: Computational Enzyme Redesign Using Transition State Analogues. PLoS ONE. 8(10). e75358–e75358. 21 indexed citations

Pantazes, Robert J., Matthew J. Grisewood, & Costas D. Maranas. (2011). Recent advances in computational protein design. Current Opinion in Structural Biology. 21(4). 467–472. 69 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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