S.C. Almo

2.2k total citations · 1 hit paper
20 papers, 1.7k citations indexed

About

S.C. Almo is a scholar working on Molecular Biology, Infectious Diseases and Cell Biology. According to data from OpenAlex, S.C. Almo has authored 20 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Infectious Diseases and 5 papers in Cell Biology. Recurrent topics in S.C. Almo's work include Cellular Mechanics and Interactions (4 papers), Tuberculosis Research and Epidemiology (3 papers) and Biochemical and Molecular Research (3 papers). S.C. Almo is often cited by papers focused on Cellular Mechanics and Interactions (4 papers), Tuberculosis Research and Epidemiology (3 papers) and Biochemical and Molecular Research (3 papers). S.C. Almo collaborates with scholars based in United States, Austria and China. S.C. Almo's co-authors include András Fiser, Roy A. Fava, Li‐Fan Lu, David Gondek, Li Wang, J. Louise Lines, Cory L. Ahonen, Yan Wang, Randolph J. Noelle and Anna Wasiuk and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and The Journal of Immunology.

In The Last Decade

S.C. Almo

20 papers receiving 1.6k citations

Hit Papers

VISTA, a novel mouse Ig s... 2011 2026 2016 2021 2011 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
S.C. Almo 723 533 442 213 202 20 1.7k
Michael Brigham‐Burke 886 1.2× 1.3k 2.5× 170 0.4× 124 0.6× 177 0.9× 30 2.6k
Gábor Pál 761 1.1× 736 1.4× 193 0.4× 155 0.7× 89 0.4× 62 1.9k
Øystein Garred 469 0.6× 1.1k 2.1× 304 0.7× 555 2.6× 256 1.3× 43 2.2k
Annette S. Kim 606 0.8× 857 1.6× 365 0.8× 571 2.7× 315 1.6× 90 2.6k
Malini Raghavan 1.2k 1.6× 1.1k 2.2× 356 0.8× 411 1.9× 77 0.4× 75 2.6k
Fabrice Agou 1.1k 1.5× 1.7k 3.1× 357 0.8× 167 0.8× 139 0.7× 53 2.8k
Frederick W. Muskett 361 0.5× 1.4k 2.7× 405 0.9× 188 0.9× 299 1.5× 59 2.3k
Martina Borghi 743 1.0× 1.8k 3.4× 490 1.1× 94 0.4× 377 1.9× 38 2.8k
Stephanie Kreis 548 0.8× 1.3k 2.5× 588 1.3× 222 1.0× 91 0.5× 53 2.3k
U.A. Ramagopal 1.0k 1.4× 1.1k 2.1× 628 1.4× 120 0.6× 111 0.5× 53 2.6k

Countries citing papers authored by S.C. Almo

Since Specialization
Citations

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

Fields of papers citing papers by S.C. Almo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.C. Almo. 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 S.C. Almo. The network helps show where S.C. Almo may publish in the future.

Co-authorship network of co-authors of S.C. Almo

This figure shows the co-authorship network connecting the top 25 collaborators of S.C. Almo. A scholar is included among the top collaborators of S.C. Almo 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 S.C. Almo. S.C. Almo 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.
Bresnick, Anne R., et al.. (2018). Advantages of Molecular Weight Identification during Native MS Screening. Planta Medica. 84(16). 1201–1212. 3 indexed citations
2.
Chavadi, Sivagami Sundaram, JoAnn M. Tufariello, Kaixia Mi, et al.. (2017). Mycobacterium tuberculosis universal stress protein Rv2623 interacts with the putative ATP binding cassette (ABC) transporter Rv1747 to regulate mycobacterial growth. PLoS Pathogens. 13(7). e1006515–e1006515. 41 indexed citations
4.
Calarese, D.A., Stanley Kimani, Sukhwinder Singh, et al.. (2014). Overexpression of MERTK Receptor Tyrosine Kinase in Epithelial Cancer Cells Drives Efferocytosis in a Gain-of-Function Capacity. Journal of Biological Chemistry. 289(37). 25737–25749. 80 indexed citations
5.
Calarese, D.A., S. Garforth, Smirnov Sv, et al.. (2014). Receptor Tyrosine Kinases, TYRO3, AXL, and MER, Demonstrate Distinct Patterns and Complex Regulation of Ligand-induced Activation. Journal of Biological Chemistry. 289(37). 25750–25763. 188 indexed citations
7.
Hazleton, Keith Z., Meng-Chiao Ho, María B. Cassera, et al.. (2012). Acyclic Immucillin Phosphonates: Second-Generation Inhibitors of Plasmodium falciparum Hypoxanthine- Guanine-Xanthine Phosphoribosyltransferase. Chemistry & Biology. 19(6). 721–730. 58 indexed citations
8.
Wang, Li, Rotem Rubinstein, J. Louise Lines, et al.. (2011). VISTA, a novel mouse Ig superfamily ligand that negatively regulates T cell responses. The Journal of Experimental Medicine. 208(3). 577–592. 558 indexed citations breakdown →
9.
Mi, Kaixia, P.W. Bilder, Meihao Sun, et al.. (2009). Mycobacterium tuberculosis Universal Stress Protein Rv2623 Regulates Bacillary Growth by ATP-Binding: Requirement for Establishing Chronic Persistent Infection. PLoS Pathogens. 5(5). e1000460–e1000460. 109 indexed citations
11.
Ball, Tanja, Birgit Linhart, Karoline Sonneck, et al.. (2009). Reducing allergenicity by altering allergen fold: a mosaic protein of Phl p 1 for allergy vaccination. Allergy. 64(4). 569–580. 30 indexed citations
12.
Vrtala, Susanne, M. Focke, J. Kopec, et al.. (2007). Genetic Engineering of the Major Timothy Grass Pollen Allergen, Phl p 6, to Reduce Allergenic Activity and Preserve Immunogenicity. The Journal of Immunology. 179(3). 1730–1739. 24 indexed citations
13.
Zhan, Chenyang, E.V. Fedorov, Wuxian Shi, et al.. (2005). The ybeY protein fromEscherichia coliis a metalloprotein. Acta Crystallographica Section F Structural Biology and Crystallization Communications. 61(11). 959–963. 34 indexed citations
14.
Shi, Wuxian, Li-Min Ting, Gregory Kicska, et al.. (2004). Plasmodium falciparum Purine Nucleoside Phosphorylase. Journal of Biological Chemistry. 279(18). 18103–18106. 94 indexed citations
15.
Mühlrád, András, Dmitri S. Kudryashov, Y. Michael Peyser, et al.. (2004). Cofilin Induced Conformational Changes in F-actin Expose Subdomain 2 to Proteolysis. Journal of Molecular Biology. 342(5). 1559–1567. 46 indexed citations
16.
Huang, Raymond Y., Simon J. Boulton, Marc Vidal, et al.. (2003). High-throughput expression, purification, and characterization of recombinant Caenorhabditis elegans proteins. Biochemical and Biophysical Research Communications. 307(4). 928–934. 14 indexed citations
17.
Apgar, Joshua F., et al.. (2000). Multiple-Particle Tracking Measurements of Heterogeneities in Solutions of Actin Filaments and Actin Bundles. Biophysical Journal. 79(2). 1095–1106. 180 indexed citations
18.
Hanein, Dorit, Niels Volkmann, Anne‐Marie Michon, et al.. (1998). An atomic model of fimbrin binding to F-actin and its implications for filament crosslinking and regulation. Nature Structural Biology. 5(9). 787–792. 108 indexed citations
19.
Hanein, Dorit, Niels Volkmann, Anne‐Marie Michon, et al.. (1998). An atomic model of fimbrin binding to F-actin and its implications forfilament crosslinking and regulation. Nature Structural Biology. 5(10). 924–924. 15 indexed citations
20.
Almo, S.C., Thomas D. Pollard, Michael Way, & Eaton E. Lattman. (1994). Purification, Characterization and Crystallization of Acanthamoeba Profilin Expressed in Escherichia coli. Journal of Molecular Biology. 236(3). 950–952. 27 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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