Abhay Jere

2.2k total citations · 1 hit paper
18 papers, 1.3k citations indexed

About

Abhay Jere is a scholar working on Molecular Biology, Virology and Infectious Diseases. According to data from OpenAlex, Abhay Jere has authored 18 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Virology and 6 papers in Infectious Diseases. Recurrent topics in Abhay Jere's work include HIV Research and Treatment (8 papers), HIV/AIDS drug development and treatment (6 papers) and HIV/AIDS Research and Interventions (5 papers). Abhay Jere is often cited by papers focused on HIV Research and Treatment (8 papers), HIV/AIDS drug development and treatment (6 papers) and HIV/AIDS Research and Interventions (5 papers). Abhay Jere collaborates with scholars based in India, Japan and United States. Abhay Jere's co-authors include Krishanpal Anamika, Srikant Verma, Shiva Kumar, Vinay K. Pathak, Priyabrata Panigrahi, Chittaranjan S. Yajnik, Himangi Lubree, A N Pandit, Caroline Fall and Suyog M. Joshi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Diabetes Care.

In The Last Decade

Abhay Jere

18 papers receiving 1.3k citations

Hit Papers

Multi-omics Data Integration, Interpretation, and Its App... 2020 2026 2022 2024 2020 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abhay Jere India 12 731 177 162 161 151 18 1.3k
Carolyn J.M. Best United States 14 827 1.1× 208 1.2× 112 0.7× 87 0.5× 71 0.5× 18 1.3k
Wolfgang M. Schmidt Austria 27 1.1k 1.5× 209 1.2× 157 1.0× 83 0.5× 47 0.3× 67 1.9k
Emily Holzinger United States 12 627 0.9× 93 0.5× 280 1.7× 118 0.7× 69 0.5× 21 1.1k
Thorsten Forster United Kingdom 24 1.1k 1.5× 240 1.4× 170 1.0× 135 0.8× 71 0.5× 53 2.2k
Pejman Mohammadi United States 19 1.1k 1.5× 257 1.5× 537 3.3× 141 0.9× 198 1.3× 35 1.8k
Jishnu Das United States 23 1.4k 1.9× 122 0.7× 272 1.7× 159 1.0× 79 0.5× 80 2.0k
Sunghyun Kang South Korea 26 1.4k 1.9× 151 0.9× 149 0.9× 105 0.7× 108 0.7× 64 2.1k
Boris Hartmann United States 18 817 1.1× 144 0.8× 194 1.2× 210 1.3× 37 0.2× 34 1.5k
Ansgar Brüning Germany 24 793 1.1× 148 0.8× 212 1.3× 102 0.6× 90 0.6× 57 1.6k
Xiaofeng Li China 24 805 1.1× 102 0.6× 127 0.8× 314 2.0× 43 0.3× 166 1.9k

Countries citing papers authored by Abhay Jere

Since Specialization
Citations

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

Fields of papers citing papers by Abhay Jere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhay Jere

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

All Works

18 of 18 papers shown
1.
Deshpande, Ashish, Vishal V. Dawkar, Sandip A. Ghuge, et al.. (2022). Transcriptional and translational perturbation in abiotic stress induced physiological activities and metabolic pathway networks in spongy tissue disorder of mango fruit. Postharvest Biology and Technology. 188. 111880–111880. 13 indexed citations
2.
Verma, Srikant, et al.. (2020). Multi-omics Data Integration, Interpretation, and Its Application. Bioinformatics and Biology Insights. 14. 3743897105–3743897105. 833 indexed citations breakdown →
3.
Singh, Vivek Kumar, et al.. (2018). Elucidating mechanistic insights into drug action for atopic dermatitis: a systems biology approach. BMC Dermatology. 18(1). 3–3. 9 indexed citations
4.
Panigrahi, Priyabrata, Abhay Jere, & Krishanpal Anamika. (2018). FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer. PLoS ONE. 13(5). e0196588–e0196588. 29 indexed citations
5.
Singh, Gulzar, et al.. (2017). CGDV: a webtool for circular visualization of genomics and transcriptomics data. BMC Genomics. 18(1). 3 indexed citations
6.
Kawakami, Eiryo, Vivek Kumar Singh, Takashi Ishii, et al.. (2016). Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways. npj Systems Biology and Applications. 2(1). 15018–15018. 24 indexed citations
7.
Singh, Vivek Kumar, et al.. (2016). Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules. PLoS ONE. 11(6). e0155419–e0155419. 9 indexed citations
8.
Marwah, Veer Singh, et al.. (2013). Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data. PLoS ONE. 8(4). e60204–e60204. 66 indexed citations
9.
Joshi, Suyog M., Dattatray Bhat, Prachi Katre, et al.. (2012). Spuriously High Prevalence of Prediabetes Diagnosed by HbA1c in Young Indians Partly Explained by Hematological Factors and Iron Deficiency Anemia. Diabetes Care. 35(4). 797–802. 87 indexed citations
10.
Jere, Abhay, et al.. (2012). Next‐generation sequencing: ready for the clinics?. Clinical Genetics. 81(6). 503–510. 95 indexed citations
11.
Jere, Abhay, Mikako Fujita, Akio Adachi, & Masako Nomaguchi. (2009). Role of HIV-1 Nef protein for virus replication in vitro. Microbes and Infection. 12(1). 65–70. 18 indexed citations
12.
Santos, André F., Esmeralda A. Soares, Abhay Jere, et al.. (2008). Conservation Patterns of HIV-1 RT Connection and RNase H Domains: Identification of New Mutations in NRTI-Treated Patients. PLoS ONE. 3(3). e1781–e1781. 47 indexed citations
13.
Delviks‐Frankenberry, Krista A., Galina N. Nikolenko, Paul L. Boyer, et al.. (2008). HIV-1 reverse transcriptase connection subdomain mutations reduce template RNA degradation and enhance AZT excision. Proceedings of the National Academy of Sciences. 105(31). 10943–10948. 49 indexed citations
14.
Tripathy, Srikanth, et al.. (2006). Molecular Analysis of gp41 Sequences of HIV Type 1 Subtype C from India. JAIDS Journal of Acquired Immune Deficiency Syndromes. 41(3). 345–351. 10 indexed citations
15.
Sakurai, Akiko, Abhay Jere, Akiko Yoshida, et al.. (2004). Functional analysis of HIV-1 vif genes derived from Japanese long-term nonprogressors and progressors for AIDS. Microbes and Infection. 6(9). 799–805. 11 indexed citations
16.
Jere, Abhay, et al.. (2004). Genetic analysis of Indian HIV-1 nef: subtyping, variability and implications. Microbes and Infection. 6(3). 279–289. 17 indexed citations
17.
Yoshida, Akiko, Akiko Sakurai, Ahmad Piroozmand, et al.. (2004). Determination of HIV-1 infectivity by lymphocytic cell lines with integrated luciferase gene. International Journal of Molecular Medicine. 14(6). 1073–6. 5 indexed citations
18.
Jere, Abhay, Ahmad Piroozmand, Srikanth Tripathy, et al.. (2004). Generation and characterization of HIV-1 clones chimeric for subtypes B and C nef. International Journal of Molecular Medicine. 14(6). 1087–90. 1 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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