Marc Jacobs

3.8k total citations · 1 hit paper
64 papers, 2.6k citations indexed

About

Marc Jacobs is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Marc Jacobs has authored 64 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 11 papers in Artificial Intelligence and 8 papers in Computational Theory and Mathematics. Recurrent topics in Marc Jacobs's work include Connexins and lens biology (14 papers), Biomedical Text Mining and Ontologies (9 papers) and Protein Kinase Regulation and GTPase Signaling (6 papers). Marc Jacobs is often cited by papers focused on Connexins and lens biology (14 papers), Biomedical Text Mining and Ontologies (9 papers) and Protein Kinase Regulation and GTPase Signaling (6 papers). Marc Jacobs collaborates with scholars based in United States, New Zealand and Germany. Marc Jacobs's co-authors include Stephen C. Harrison, Paul J. Donaldson, Lora Swenson, Mark Fleming, Robert O. Fox, Brian Hare, Albert C. Pierce, Paul Taslimi, Joerg Kistler and Christian Soeller and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Marc Jacobs

60 papers receiving 2.5k citations

Hit Papers

Structure of an IκBα/NF-κ... 1998 2026 2007 2016 1998 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Marc Jacobs 1.6k 409 330 325 269 64 2.6k
David L. Selwood 1.9k 1.1× 394 1.0× 628 1.9× 223 0.7× 373 1.4× 100 3.7k
Chaohong Sun 2.8k 1.7× 399 1.0× 235 0.7× 245 0.8× 524 1.9× 46 3.6k
Monica Schenone 2.7k 1.6× 345 0.8× 254 0.8× 399 1.2× 604 2.2× 33 3.5k
Ricardo M. Biondi 3.4k 2.1× 190 0.5× 276 0.8× 340 1.0× 329 1.2× 79 4.1k
Kathleen A. Gallo 2.2k 1.4× 281 0.7× 124 0.4× 297 0.9× 411 1.5× 71 3.3k
Mario A. Pagano 1.9k 1.1× 206 0.5× 316 1.0× 91 0.3× 368 1.4× 70 2.8k
Andrew M. Petros 3.4k 2.1× 454 1.1× 318 1.0× 328 1.0× 659 2.4× 60 4.4k
George M. Spyrou 1.6k 1.0× 203 0.5× 162 0.5× 224 0.7× 297 1.1× 165 3.0k
Thomas O’Brien 2.7k 1.6× 225 0.6× 364 1.1× 337 1.0× 743 2.8× 62 3.6k
Scott A. Busby 2.4k 1.5× 285 0.7× 134 0.4× 224 0.7× 344 1.3× 37 3.6k

Countries citing papers authored by Marc Jacobs

Since Specialization
Citations

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

Fields of papers citing papers by Marc Jacobs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marc Jacobs

This figure shows the co-authorship network connecting the top 25 collaborators of Marc Jacobs. A scholar is included among the top collaborators of Marc Jacobs 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 Marc Jacobs. Marc Jacobs 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
2.
Shen, Jian, et al.. (2025). Algorithms in the orchard: An embedding-based expert answering system for apple rust. Smart Agricultural Technology. 12. 101069–101069.
3.
Schultz, Bruce, et al.. (2024). Rationalism in the face of GPT hypes: Benchmarking the output of large language models against human expert-curated biomedical knowledge graphs. SHILAP Revista de lepidopterología. 5. 100095–100095. 4 indexed citations
4.
Gribbon, Philip, et al.. (2024). Current state of data stewardship tools in life science. Frontiers in Big Data. 7. 1428568–1428568. 1 indexed citations
5.
Russo, Maria Francesca, Daniel Domingo‐Fernándéz, Andrea Zaliani, et al.. (2024). Curating, Collecting, and Cataloguing Global COVID-19 Datasets for the Aim of Predicting Personalized Risk. Data. 9(2). 25–25.
6.
Gebel, Stephan, Bruce Schultz, Marc Jacobs, et al.. (2023). The Epilepsy Ontology: a community-based ontology tailored for semantic interoperability and text mining. Bioinformatics Advances. 3(1). vbad033–vbad033. 2 indexed citations
7.
Schultz, Bruce, Andrea Zaliani, Stephan Gebel, et al.. (2022). A hybrid approach unveils drug repurposing candidates targeting an Alzheimer pathophysiology mechanism. Patterns. 3(3). 100433–100433. 10 indexed citations
8.
Jacobs, Marc, et al.. (2022). Common data model for COVID-19 datasets. Bioinformatics. 38(24). 5466–5468. 3 indexed citations
9.
Cursons, Joseph, Catherine E. Angel, Daniel Hurley, et al.. (2015). Spatially transformed fluorescence image data for ERK-MAPK and selected proteins within human epidermis. GigaScience. 4(1). 63–63. 5 indexed citations
10.
Byrn, Randal A., Steven J.M. Jones, Michael P. Clark, et al.. (2014). Preclinical Activity of VX-787, a First-in-Class, Orally Bioavailable Inhibitor of the Influenza Virus Polymerase PB2 Subunit. Antimicrobial Agents and Chemotherapy. 59(3). 1569–1582. 149 indexed citations
11.
Grey, Angus C., Ling Li, Marc Jacobs, Kevin L. Schey, & Paul J. Donaldson. (2009). Differentiation-dependent modification and subcellular distribution of aquaporin-0 suggests multiple functional roles in the rat lens. Differentiation. 77(1). 70–83. 35 indexed citations
12.
Vaghefi, Ehsan, Beau Pontré, Paul J. Donaldson, Peter Hunter, & Marc Jacobs. (2009). Visualization of transverse diffusion paths across fiber cells of the ocular lens by small animal MRI. Physiological Measurement. 30(10). 1061–1073. 19 indexed citations
13.
Jacobs, Marc. (2009). Multiscale systems integration in the eye. WIREs Systems Biology and Medicine. 1(1). 15–27. 5 indexed citations
14.
Doran, John & Marc Jacobs. (2008). ROCK Enzymatic Assay. Methods in molecular biology. 468. 197–205. 1 indexed citations
15.
Jacobs, Marc, Olga Futer, Lora Swenson, et al.. (2005). Pim-1 Ligand-bound Structures Reveal the Mechanism of Serine/Threonine Kinase Inhibition by LY294002. Journal of Biological Chemistry. 280(14). 13728–13734. 163 indexed citations
16.
Jacobs, Marc, et al.. (2004). Gap junction processing and redistribution revealed by quantitative optical measurements of connexin46 epitopes in the lens.: Investigative ophthalmology & visual science. Investigative Ophthalmology & Visual Science. 45(1). 191–199. 1 indexed citations
17.
Moore, Jonathan M., Norzehan Abdul-Manan, Jasna Fejzo, et al.. (2003). Leveraging structural approaches: applications of NMR-based screening and X-ray crystallography for inhibitor design. Journal of Synchrotron Radiation. 11(1). 97–100. 21 indexed citations
18.
Lepre, Christopher A., Jeffrey W. Peng, Jasna Fejzo, et al.. (2002). Applications of SHAPES Screening in Drug Discovery. Combinatorial Chemistry & High Throughput Screening. 5(8). 583–590. 37 indexed citations
19.
Gonen, Tamir, Angus C. Grey, Marc Jacobs, Paul J. Donaldson, & Joerg Kistler. (2001). MP20, the second most abundant lens membrane protein and member of the tetraspanin superfamily, joins the list of ligands of galectin-3. BMC Cell Biology. 2(1). 17–17. 35 indexed citations
20.
Jacobs, Marc & Stephen C. Harrison. (1998). Structure of an IκBα/NF-κB Complex. Cell. 95(6). 749–758. 706 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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