Samuel DeLuca

888 total citations
8 papers, 632 citations indexed

About

Samuel DeLuca is a scholar working on Molecular Biology, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Samuel DeLuca has authored 8 papers receiving a total of 632 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Samuel DeLuca's work include Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Samuel DeLuca is often cited by papers focused on Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Samuel DeLuca collaborates with scholars based in United States and Russia. Samuel DeLuca's co-authors include Jens Meiler, Jonathan H. Sheehan, Gordon Lemmon, Kristian Kaufmann, Karen R. Khar, Jordan R. Willis, D.P. Nannemann, Steven A. Combs, Elizabeth D. Nguyen and Bryan Briney and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biochemistry.

In The Last Decade

Samuel DeLuca

8 papers receiving 624 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Samuel DeLuca United States	6	458	117	84	76	47	8	632
Edoardo Milanetti Italy	20	592 1.3×	107 0.9×	103 1.2×	127 1.7×	55 1.2×	65	934
Roland A. Pache Spain	12	580 1.3×	104 0.9×	66 0.8×	80 1.1×	27 0.6×	19	703
Jörg Schaarschmidt Germany	13	560 1.2×	136 1.2×	55 0.7×	127 1.7×	43 0.9×	23	852
Elke Michalsky Germany	12	384 0.8×	104 0.9×	45 0.5×	78 1.0×	60 1.3×	18	524
Gyu Rie Lee South Korea	14	748 1.6×	148 1.3×	99 1.2×	122 1.6×	60 1.3×	23	909
Richard A. George United Kingdom	13	725 1.6×	110 0.9×	69 0.8×	76 1.0×	39 0.8×	17	875
Christina Schindler Germany	15	676 1.5×	149 1.3×	60 0.7×	167 2.2×	43 0.9×	25	822
Jiayi Dou United States	10	695 1.5×	206 1.8×	104 1.2×	104 1.4×	25 0.5×	12	866
Coos Baakman Netherlands	7	799 1.7×	183 1.6×	50 0.6×	93 1.2×	37 0.8×	10	1.0k
Lorenzo Di Rienzo Italy	15	383 0.8×	105 0.9×	70 0.8×	102 1.3×	24 0.5×	39	578

Countries citing papers authored by Samuel DeLuca

Since Specialization

Citations

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

Fields of papers citing papers by Samuel DeLuca

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel DeLuca

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

All Works

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8 of 8 papers shown

1.

DeLuca, Samuel, Karen R. Khar, & Jens Meiler. (2015). Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand. PLoS ONE. 10(7). e0132508–e0132508. 95 indexed citations

2.

DeLuca, Samuel, et al.. (2015). RosettaTMH: a method for membrane protein structure elucidation combining EPR distance restraints with assembly of transmembrane helices. SHILAP Revista de lepidopterología. 3(1). 1–26. 1 indexed citations

3.

Austin, Thomas M., D.P. Nannemann, Samuel DeLuca, Jens Meiler, & Eric Delpire. (2014). In silico analysis and experimental verification of OSR1 kinase – Peptide interaction. Journal of Structural Biology. 187(1). 58–65. 4 indexed citations

4.

Handschuh, Robert F., et al.. (2014). Vibration and Operational Characteristics of a Composite-Steel (Hybrid) Gear. NASA Technical Reports Server (NASA). 13 indexed citations

5.

Combs, Steven A., Samuel DeLuca, Gordon Lemmon, et al.. (2013). Small-molecule ligand docking into comparative models with Rosetta. Nature Protocols. 8(7). 1277–1298. 134 indexed citations

6.

Willis, Jordan R., Bryan Briney, Samuel DeLuca, James E. Crowe, & Jens Meiler. (2013). Human Germline Antibody Gene Segments Encode Polyspecific Antibodies. PLoS Computational Biology. 9(4). e1003045–e1003045. 66 indexed citations

7.

DeLuca, Samuel, Brent M. Dorr, & Jens Meiler. (2011). Design of Native-like Proteins through an Exposure-Dependent Environment Potential. Biochemistry. 50(40). 8521–8528. 10 indexed citations

8.

Kaufmann, Kristian, Gordon Lemmon, Samuel DeLuca, Jonathan H. Sheehan, & Jens Meiler. (2010). Practically Useful: What the R osetta Protein Modeling Suite Can Do for You. Biochemistry. 49(14). 2987–2998. 309 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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