Ekampreet Singh

629 total citations
15 papers, 407 citations indexed

About

Ekampreet Singh is a scholar working on Molecular Biology, Computational Theory and Mathematics and Molecular Medicine. According to data from OpenAlex, Ekampreet Singh has authored 15 papers receiving a total of 407 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 5 papers in Molecular Medicine. Recurrent topics in Ekampreet Singh's work include Computational Drug Discovery Methods (7 papers), Antibiotic Resistance in Bacteria (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Ekampreet Singh is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Antibiotic Resistance in Bacteria (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Ekampreet Singh collaborates with scholars based in India, Italy and Ethiopia. Ekampreet Singh's co-authors include Amit Kumar Singh, Jayaraman Muthukumaran, Monika Jain, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Rashmi Prabha Singh, Amita Pathak, Ankit Kumar and Nitish Kumar and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Archives of Biochemistry and Biophysics.

In The Last Decade

Ekampreet Singh

15 papers receiving 401 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ekampreet Singh India 8 234 196 136 78 40 15 407
Rajat Kumar Jha India 9 257 1.1× 205 1.0× 157 1.2× 84 1.1× 39 1.0× 16 448
Rameez Jabeer Khan India 10 263 1.1× 206 1.1× 165 1.2× 85 1.1× 40 1.0× 16 454
Gizachew Muluneh Amera India 10 251 1.1× 200 1.0× 164 1.2× 79 1.0× 38 0.9× 12 451
Salman Ali Khan Pakistan 8 200 0.9× 207 1.1× 153 1.1× 79 1.0× 32 0.8× 24 422
Komal Zia Pakistan 9 222 0.9× 190 1.0× 164 1.2× 97 1.2× 37 0.9× 18 497
Amita Pathak India 10 211 0.9× 160 0.8× 165 1.2× 64 0.8× 35 0.9× 13 402
Ammar D. Elmezayen Türkiye 7 268 1.1× 211 1.1× 146 1.1× 79 1.0× 39 1.0× 9 446
Rajib Islam Bangladesh 6 276 1.2× 195 1.0× 211 1.6× 88 1.1× 47 1.2× 8 539
Rashmi Prabha Singh India 7 211 0.9× 189 1.0× 121 0.9× 91 1.2× 36 0.9× 17 486
Md. Rimon Parves Bangladesh 9 266 1.1× 183 0.9× 235 1.7× 95 1.2× 49 1.2× 13 566

Countries citing papers authored by Ekampreet Singh

Since Specialization
Citations

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

Fields of papers citing papers by Ekampreet Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ekampreet Singh

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

All Works

15 of 15 papers shown
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2.
Khan, Rameez Jabeer, Ekampreet Singh, Rajat Kumar Jha, et al.. (2023). Identification and prioritization of potential therapeutic molecules against LpxA from Acinetobacter baumannii – A computational study. SHILAP Revista de lepidopterología. 5. 100096–100096. 7 indexed citations
3.
4.
Singh, Ekampreet, et al.. (2023). Molecular dynamics simulations assisted investigation of phytochemicals as potential lead candidates against anti-apoptotic Bcl-B protein. Journal of Biomolecular Structure and Dynamics. 43(6). 3049–3063. 5 indexed citations
5.
Ali, Mohd Sajid, Ekampreet Singh, Jayaraman Muthukumaran, & Hamad A. Al‐Lohedan. (2023). Non-Steroidal Anti-Inflammatory Drug Effect on the Binding of Plasma Protein with Antibiotic Drug Ceftazidime: Spectroscopic and In Silico Investigation. International Journal of Molecular Sciences. 24(19). 14811–14811. 1 indexed citations
6.
Kumar, Ankit, Ekampreet Singh, Rajat Kumar Jha, et al.. (2023). Targeting multi-drug-resistant Acinetobacter baumannii: a structure-based approach to identify the promising lead candidates against glutamate racemase. Journal of Molecular Modeling. 29(6). 188–188. 4 indexed citations
7.
Kumar, Nitish, et al.. (2023). Pathology, target discovery, and the evolution of XO inhibitors from the first discovery to recent advances (2020–2023). Bioorganic Chemistry. 143. 107042–107042. 7 indexed citations
8.
Jha, Rajat Kumar, Ekampreet Singh, Rameez Jabeer Khan, et al.. (2022). Droperidol as a potential inhibitor of acyl-homoserine lactone synthase from A. baumannii: insights from virtual screening, MD simulations and MM/PBSA calculations. Molecular Diversity. 27(5). 1979–1999. 1 indexed citations
9.
Jha, Rajat Kumar, Rameez Jabeer Khan, Ekampreet Singh, et al.. (2022). An extensive computational study to identify potential inhibitors of Acyl-homoserine-lactone synthase from Acinetobacter baumannii (strain AYE). Journal of Molecular Graphics and Modelling. 114. 108168–108168. 7 indexed citations
10.
Singh, Ekampreet, Rajat Kumar Jha, Rameez Jabeer Khan, et al.. (2022). A computational essential dynamics approach to investigate structural influences of ligand binding on Papain like protease from SARS-CoV-2. Computational Biology and Chemistry. 99. 107721–107721. 14 indexed citations
11.
Jha, Rajat Kumar, Rameez Jabeer Khan, A. Parthiban, et al.. (2021). Identifying the natural compound Catechin from tropical mangrove plants as a potential lead candidate against 3CL pro from SARS-CoV-2: An integrated in silico approach. Journal of Biomolecular Structure and Dynamics. 40(24). 13392–13411. 5 indexed citations
12.
Khan, Rameez Jabeer, Rajat Kumar Jha, Ekampreet Singh, et al.. (2020). Identification of promising antiviral drug candidates against non-structural protein 15 (NSP15) from SARS-CoV-2: an in silico assisted drug-repurposing study. Journal of Biomolecular Structure and Dynamics. 40(1). 438–448. 26 indexed citations
13.
Singh, Ekampreet, Rameez Jabeer Khan, Rajat Kumar Jha, et al.. (2020). A comprehensive review on promising anti-viral therapeutic candidates identified against main protease from SARS-CoV-2 through various computational methods. Journal of Genetic Engineering and Biotechnology. 18(1). 69–69. 40 indexed citations
14.
Jha, Rajat Kumar, Rameez Jabeer Khan, Gizachew Muluneh Amera, et al.. (2020). Identification of promising molecules against MurD ligase from Acinetobacter baumannii: insights from comparative protein modelling, virtual screening, molecular dynamics simulations and MM/PBSA analysis. Journal of Molecular Modeling. 26(11). 304–304. 19 indexed citations
15.
Khan, Rameez Jabeer, Rajat Kumar Jha, Gizachew Muluneh Amera, et al.. (2020). Targeting SARS-CoV-2: a systematic drug repurposing approach to identify promising inhibitors against 3C-like proteinase and 2′-O-ribose methyltransferase. Journal of Biomolecular Structure and Dynamics. 39(8). 2679–2692. 262 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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