Akila Jayaraman

1.1k total citations
20 papers, 859 citations indexed

About

Akila Jayaraman is a scholar working on Epidemiology, Immunology and Molecular Biology. According to data from OpenAlex, Akila Jayaraman has authored 20 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Epidemiology, 7 papers in Immunology and 5 papers in Molecular Biology. Recurrent topics in Akila Jayaraman's work include Influenza Virus Research Studies (17 papers), Respiratory viral infections research (14 papers) and Immune Response and Inflammation (6 papers). Akila Jayaraman is often cited by papers focused on Influenza Virus Research Studies (17 papers), Respiratory viral infections research (14 papers) and Immune Response and Inflammation (6 papers). Akila Jayaraman collaborates with scholars based in United States, Singapore and Canada. Akila Jayaraman's co-authors include Ram Sasisekharan, Rahul Raman, Karthik Viswanathan, Claudia Pappas, Terrence M. Tumpey, Kannan Tharakaraman, Zachary Shriver, Hui Zeng, V. Sasisekharan and Jessica A. Belser and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Akila Jayaraman

20 papers receiving 843 citations

Peers

Akila Jayaraman

EPIDE

ACS

IMMUN

Louis M. Schwartzman United States

Siu-Ying Lau Hong Kong

Ruvim Izikson United States

Diane Niño United States

A. S. Gambaryan Russia

Rebecca Frise United Kingdom

Alita Kongchanagul Thailand

Marine L. B. Hillaire Netherlands

Irina Isakova–Sivak Russia

Ornpreya Suptawiwat Thailand

Louis M. Schwartzman United States

Akila Jayaraman

968 ×1.3

EPIDE

166 ×0.6

ACS

257 ×0.9

338 ×1.8

426 ×2.5

IMMUN

Citations per year, relative to Akila Jayaraman Akila Jayaraman (= 1×) peers Louis M. Schwartzman

Countries citing papers authored by Akila Jayaraman

Since Specialization

Citations

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

Fields of papers citing papers by Akila Jayaraman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akila Jayaraman

This figure shows the co-authorship network connecting the top 25 collaborators of Akila Jayaraman. A scholar is included among the top collaborators of Akila Jayaraman 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 Akila Jayaraman. Akila Jayaraman 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

Clark, Thomas A., Vidya Subramanian, Akila Jayaraman, et al.. (2023). Enhancing antibody affinity through experimental sampling of non-deleterious CDR mutations predicted by machine learning. Communications Chemistry. 6(1). 244–244. 14 indexed citations

Jayaraman, Akila, et al.. (2022). Optimizing Antibody Affinity and Developability Using a Framework–CDR Shuffling Approach—Application to an Anti-SARS-CoV-2 Antibody. Viruses. 14(12). 2694–2694. 7 indexed citations

Jayaraman, Akila, et al.. (2021). Orthogonal immunoassays for IgG antibodies to SARS-CoV-2 antigens reveal that immune response lasts beyond 4 mo post illness onset. Proceedings of the National Academy of Sciences. 118(5). 18 indexed citations

Lakdawala, Seema S., Akila Jayaraman, Rebecca Halpin, et al.. (2015). The soft palate is an important site of adaptation for transmissible influenza viruses. Nature. 526(7571). 122–125. 124 indexed citations

Raman, Rahul, Kannan Tharakaraman, Akila Jayaraman, et al.. (2014). Glycan receptor specificity as a useful tool for characterization and surveillance of influenza A virus. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations

Raman, Rahul, Kannan Tharakaraman, Zachary Shriver, et al.. (2014). Glycan receptor specificity as a useful tool for characterization and surveillance of influenza A virus. Trends in Microbiology. 22(11). 632–641. 24 indexed citations

Tharakaraman, Kannan, Akila Jayaraman, Rahul Raman, et al.. (2013). Glycan Receptor Binding of the Influenza A Virus H7N9 Hemagglutinin. Cell. 153(7). 1486–1493. 107 indexed citations

Raman, Rahul, et al.. (2013). Quantitative Description of Glycan-Receptor Binding of Influenza A Virus H7 Hemagglutinin. PLoS ONE. 8(2). e49597–e49597. 46 indexed citations

Raman, Rahul, et al.. (2013). Quantitative Characterization of Glycan-Receptor Binding of H9N2 Influenza A Virus Hemagglutinin. PLoS ONE. 8(4). e59550–e59550. 16 indexed citations

10.

Tharakaraman, Kannan, Rahul Raman, Karthik Viswanathan, et al.. (2013). Structural Determinants for Naturally Evolving H5N1 Hemagglutinin to Switch Its Receptor Specificity. Cell. 153(7). 1475–1485. 64 indexed citations

11.

Lakdawala, Seema S., Angela Shih, Akila Jayaraman, et al.. (2013). Receptor specificity does not affect replication or virulence of the 2009 pandemic H1N1 influenza virus in mice and ferrets. Virology. 446(1-2). 349–356. 18 indexed citations

12.

Sun, Xiangjie, Akila Jayaraman, Rahul Raman, et al.. (2013). N-Linked Glycosylation of the Hemagglutinin Protein Influences Virulence and Antigenicity of the 1918 Pandemic and Seasonal H1N1 Influenza A Viruses. Journal of Virology. 87(15). 8756–8766. 76 indexed citations

13.

Raman, Rahul, et al.. (2013). Correction: Quantitative Description of Glycan-Receptor Binding of Influenza A Virus H7 Hemagglutinin. PLoS ONE. 8(12). 6 indexed citations

14.

Jayaraman, Akila, Aarthi Chandrasekaran, Karthik Viswanathan, et al.. (2012). Decoding the Distribution of Glycan Receptors for Human-Adapted Influenza A Viruses in Ferret Respiratory Tract. PLoS ONE. 7(2). e27517–e27517. 64 indexed citations

15.

Jayaraman, Akila, Xiaoying Koh, Jing Li, et al.. (2012). Glycosylation at Asn91 of H1N1 haemagglutinin affects binding to glycan receptors. Biochemical Journal. 444(3). 429–435. 22 indexed citations

16.

Pearce, Melissa B., Akila Jayaraman, Claudia Pappas, et al.. (2012). Pathogenesis and transmission of swine origin A(H3N2)v influenza viruses in ferrets. Proceedings of the National Academy of Sciences. 109(10). 3944–3949. 105 indexed citations

17.

Belser, Jessica A., Akila Jayaraman, Rahul Raman, et al.. (2011). Effect of D222G Mutation in the Hemagglutinin Protein on Receptor Binding, Pathogenesis and Transmissibility of the 2009 Pandemic H1N1 Influenza Virus. PLoS ONE. 6(9). e25091–e25091. 70 indexed citations

18.

Jayaraman, Akila, Claudia Pappas, Rahul Raman, et al.. (2011). A Single Base-Pair Change in 2009 H1N1 Hemagglutinin Increases Human Receptor Affinity and Leads to Efficient Airborne Viral Transmission in Ferrets. PLoS ONE. 6(3). e17616–e17616. 51 indexed citations

19.

Hensley, Scott E., S. R. Das, Ashley Bailey, et al.. (2009). Hemagglutinin Receptor Binding Avidity Drives Influenza A Virus Antigenic Drift. Science. 326(5953). 734–736. 7 indexed citations

20.

Maines, Taronna R., Akila Jayaraman, Jessica A. Belser, et al.. (2009). Transmission and Pathogenesis of Swine-Origin 2009 A(H1N1) Influenza Viruses in Ferrets and Mice. Science. 325(5939). 484–487. 19 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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