Vikram Khipple Mulligan

6.5k total citations · 4 hit papers
32 papers, 3.0k citations indexed

About

Vikram Khipple Mulligan is a scholar working on Molecular Biology, Materials Chemistry and Neurology. According to data from OpenAlex, Vikram Khipple Mulligan has authored 32 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 6 papers in Materials Chemistry and 5 papers in Neurology. Recurrent topics in Vikram Khipple Mulligan's work include Protein Structure and Dynamics (13 papers), RNA and protein synthesis mechanisms (9 papers) and Chemical Synthesis and Analysis (8 papers). Vikram Khipple Mulligan is often cited by papers focused on Protein Structure and Dynamics (13 papers), RNA and protein synthesis mechanisms (9 papers) and Chemical Synthesis and Analysis (8 papers). Vikram Khipple Mulligan collaborates with scholars based in United States, Canada and Germany. Vikram Khipple Mulligan's co-authors include David Baker, Frank DiMaio, Hahnbeom Park, Philip Bradley, Avijit Chakrabartty, David E. Kim, Jason W. Labonte, Richard Bonneau, P. Douglas Renfrew and Jeliazko R. Jeliazkov and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Vikram Khipple Mulligan

32 papers receiving 3.0k 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.

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

2017 942 citations Rebecca F. Alford, Andrew Leaver‐Fay et al. Journal of Chemical Theory and Computation profile →
Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules

2016 352 citations Hahnbeom Park, Philip Bradley et al. Journal of Chemical Theory and Computation profile →
Global analysis of protein folding using massively parallel design, synthesis, and testing

2017 305 citations Sugyan M. Dixit, Tamuka M. Chidyausiku et al. Science profile →
De novo design of bioactive protein switches

2019 185 citations Robert A. Langan, Scott E. Boyken et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vikram Khipple Mulligan United States	20	2.5k	494	315	214	183	32	3.0k
Stuart A. Sievers United States	17	3.0k 1.2×	585 1.2×	189 0.6×	292 1.4×	465 2.5×	24	4.4k
Glen Spraggon United States	37	2.3k 1.0×	466 0.9×	179 0.6×	147 0.7×	454 2.5×	70	4.0k
Kannan Gunasekaran United States	24	2.5k 1.0×	730 1.5×	487 1.5×	283 1.3×	202 1.1×	39	2.9k
Cyril Dominguez United Kingdom	19	4.0k 1.7×	561 1.1×	229 0.7×	406 1.9×	301 1.6×	34	4.6k
F. Niesen United Kingdom	19	2.7k 1.1×	443 0.9×	219 0.7×	209 1.0×	422 2.3×	25	3.5k
Kaare Teilum Denmark	30	2.3k 0.9×	858 1.7×	152 0.5×	133 0.6×	157 0.9×	73	3.1k
Indraneel Ghosh United States	31	2.7k 1.1×	391 0.8×	307 1.0×	129 0.6×	218 1.2×	64	3.5k
Irina S. Moreira Portugal	26	2.1k 0.9×	379 0.8×	302 1.0×	539 2.5×	206 1.1×	86	2.7k
Ian Walsh Singapore	25	2.2k 0.9×	510 1.0×	155 0.5×	144 0.7×	71 0.4×	57	2.5k
Michał J. Gajda Germany	12	2.0k 0.8×	732 1.5×	90 0.3×	116 0.5×	129 0.7×	21	2.7k

Countries citing papers authored by Vikram Khipple Mulligan

Since Specialization

Citations

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

Fields of papers citing papers by Vikram Khipple Mulligan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikram Khipple Mulligan. 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 Vikram Khipple Mulligan. The network helps show where Vikram Khipple Mulligan may publish in the future.

Co-authorship network of co-authors of Vikram Khipple Mulligan

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

All Works

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20 of 20 papers shown

Mulligan, Vikram Khipple, Jack B. Maguire, Sergey Lyskov, et al.. (2024). Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins. PLoS Computational Biology. 20(3). e1011939–e1011939. 12 indexed citations

Chorsi, Meysam T., Alexandra Pozhidaeva, Vikram Khipple Mulligan, et al.. (2024). Ultra-confined controllable cyclic peptides as supramolecular biomaterials. Nano Today. 56. 102247–102247. 5 indexed citations

Maguire, Jack B., et al.. (2021). XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers. PLoS Computational Biology. 17(9). e1009037–e1009037. 11 indexed citations

Hosseinzadeh, Parisa, P. R. Watson, Timothy W. Craven, et al.. (2021). Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites. Nature Communications. 12(1). 3384–3384. 45 indexed citations

Yachnin, Brahm J., Vikram Khipple Mulligan, Sagar D. Khare, & Chris Bailey‐Kellogg. (2021). MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform. Journal of Chemical Information and Modeling. 61(5). 2368–2382. 13 indexed citations

Mulligan, Vikram Khipple. (2020). The emerging role of computational design in peptide macrocycle drug discovery. Expert Opinion on Drug Discovery. 15(7). 833–852. 34 indexed citations

Langan, Robert A., Scott E. Boyken, Andrew H. Ng, et al.. (2019). De novo design of bioactive protein switches. Nature. 572(7768). 205–210. 185 indexed citations breakdown →

Lu, Peilong, Duyoung Min, Frank DiMaio, et al.. (2018). Accurate computational design of multipass transmembrane proteins. Science. 359(6379). 1042–1046. 137 indexed citations

Chen, Zibo, Scott E. Boyken, Mengxuan Jia, et al.. (2018). Programmable design of orthogonal protein heterodimers. Nature. 565(7737). 106–111. 128 indexed citations

10.

Hosseinzadeh, Parisa, Gaurav Bhardwaj, Vikram Khipple Mulligan, et al.. (2017). Comprehensive computational design of ordered peptide macrocycles. Science. 358(6369). 1461–1466. 156 indexed citations

11.

Dixit, Sugyan M., Tamuka M. Chidyausiku, Inna Goreshnik, et al.. (2017). Global analysis of protein folding using massively parallel design, synthesis, and testing. Science. 357(6347). 168–175. 305 indexed citations breakdown →

12.

Alford, Rebecca F., Andrew Leaver‐Fay, Jeliazko R. Jeliazkov, et al.. (2017). The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design. Journal of Chemical Theory and Computation. 13(6). 3031–3048. 942 indexed citations breakdown →

13.

Dang, Bobo, Haifan Wu, Vikram Khipple Mulligan, et al.. (2017). De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures. Proceedings of the National Academy of Sciences. 114(41). 10852–10857. 47 indexed citations

14.

Mills, Jeremy H., Sagar D. Khare, Jill M. Bolduc, et al.. (2013). Computational Design of an Unnatural Amino Acid Dependent Metalloprotein with Atomic Level Accuracy. Journal of the American Chemical Society. 135(36). 13393–13399. 94 indexed citations

15.

Macgregor, Robert B., et al.. (2012). Concentration-Dependent Structural Transitions of Human Telomeric DNA Sequences. Biophysical Journal. 102(3). 276a–277a. 11 indexed citations

16.

Mulligan, Vikram Khipple, et al.. (2011). Analyzing complicated protein folding kinetics rapidly by analytical Laplace inversion using a Tikhonov regularization variant. Analytical Biochemistry. 421(1). 181–190. 8 indexed citations

17.

Ceccarelli, Derek F., Rob C. Laister, Vikram Khipple Mulligan, et al.. (2011). CCM3/PDCD10 Heterodimerizes with Germinal Center Kinase III (GCKIII) Proteins Using a Mechanism Analogous to CCM3 Homodimerization. Journal of Biological Chemistry. 286(28). 25056–25064. 57 indexed citations

18.

Mulligan, Vikram Khipple, et al.. (2011). ALS-Causing SOD1 Mutations Promote Production of Copper-Deficient Misfolded Species. Journal of Molecular Biology. 409(5). 839–852. 31 indexed citations

19.

Arslan, Pharhad Eli, Vikram Khipple Mulligan, Sylvia Ho, & Avijit Chakrabartty. (2009). Conversion of Aβ42 into a Folded Soluble Native-like Protein using a Semi-random Library of Amphipathic Helices. Journal of Molecular Biology. 396(5). 1284–1294. 9 indexed citations

20.

D’Alterio, Cecilia, et al.. (2005). Drosophila melanogaster Cad99C, the orthologue of human Usher cadherin PCDH15, regulates the length of microvilli. The Journal of Cell Biology. 171(3). 549–558. 59 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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