Rajib Islam

689 total citations · 1 hit paper
8 papers, 539 citations indexed

About

Rajib Islam is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Rajib Islam has authored 8 papers receiving a total of 539 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Infectious Diseases, 5 papers in Computational Theory and Mathematics and 4 papers in Organic Chemistry. Recurrent topics in Rajib Islam's work include SARS-CoV-2 and COVID-19 Research (5 papers), Computational Drug Discovery Methods (5 papers) and Influenza Virus Research Studies (3 papers). Rajib Islam is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (5 papers), Computational Drug Discovery Methods (5 papers) and Influenza Virus Research Studies (3 papers). Rajib Islam collaborates with scholars based in Bangladesh, United States and China. Rajib Islam's co-authors include Mohammad A. Halim, Muhammad Ali, Abdulla Al Mamun, Md Nayeem Hossain, Md. Rimon Parves, Nizam Uddin, Md Sajjadur Rahman, Mohammed Akhter Hossain, M. Obayed Ullah and Md. Imran Hossain and has published in prestigious journals such as The Journal of Physical Chemistry B, Computers in Biology and Medicine and Journal of Biomolecular Structure and Dynamics.

In The Last Decade

Rajib Islam

8 papers receiving 532 citations

Hit Papers

A molecular modeling approach to identify effective antiv... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rajib Islam Bangladesh 6 276 211 195 88 47 8 539
Abdulla Al Mamun United States 10 274 1.0× 203 1.0× 178 0.9× 95 1.1× 48 1.0× 22 597
Md. Rimon Parves Bangladesh 9 266 1.0× 235 1.1× 183 0.9× 95 1.1× 49 1.0× 13 566
Amit Kumar Singh India 12 273 1.0× 233 1.1× 212 1.1× 91 1.0× 45 1.0× 39 595
Komal Zia Pakistan 9 222 0.8× 164 0.8× 190 1.0× 97 1.1× 37 0.8× 18 497
Salman Ali Khan Pakistan 8 200 0.7× 153 0.7× 207 1.1× 79 0.9× 32 0.7× 24 422
Mikołaj Żmudziński Poland 8 325 1.2× 282 1.3× 394 2.0× 115 1.3× 41 0.9× 9 699
Ammar D. Elmezayen Türkiye 7 268 1.0× 146 0.7× 211 1.1× 79 0.9× 39 0.8× 9 446
Weijuan Shang China 15 228 0.8× 217 1.0× 301 1.5× 137 1.6× 46 1.0× 26 704
Gizachew Muluneh Amera India 10 251 0.9× 164 0.8× 200 1.0× 79 0.9× 38 0.8× 12 451
Arif Ali China 13 257 0.9× 404 1.9× 297 1.5× 46 0.5× 52 1.1× 24 747

Countries citing papers authored by Rajib Islam

Since Specialization
Citations

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

Fields of papers citing papers by Rajib Islam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajib Islam

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

All Works

8 of 8 papers shown
1.
Stewart, James T., Muhammad Ali, Rajib Islam, et al.. (2023). Antiviral peptides inhibiting the main protease of SARS‐CoV‐2 investigated by computational screening and in vitro protease assay. Journal of Peptide Science. 30(4). 2 indexed citations
2.
Hossain, Imtiaz, Muhammad Ali, Md. Abdul Kaium, et al.. (2022). Potential antiviral peptides against the nucleoprotein of SARS-CoV-2. Chemical Papers. 77(2). 813–823. 2 indexed citations
3.
Islam, Md. Aminul, et al.. (2021). Computational screening of 645 antiviral peptides against the receptor-binding domain of the spike protein in SARS-CoV-2. Computers in Biology and Medicine. 136. 104759–104759. 37 indexed citations
4.
Mamun, Abdulla Al, Rajib Islam, Md Nayeem Hossain, et al.. (2020). Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 39(16). 6290–6305. 37 indexed citations
5.
Islam, Rajib, Md. Rimon Parves, Nizam Uddin, et al.. (2020). A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 39(9). 1–12. 269 indexed citations breakdown →
6.
Islam, Rajib, et al.. (2020). Virtual screening, molecular dynamics and structure–activity relationship studies to identify potent approved drugs for Covid-19 treatment. Journal of Biomolecular Structure and Dynamics. 39(16). 6231–6241. 92 indexed citations
7.
Ali, Muhammad, Rajib Islam, Md. Rimon Parves, et al.. (2020). Antiviral Peptides as Promising Therapeutics against SARS-CoV-2. The Journal of Physical Chemistry B. 124(44). 9785–9792. 75 indexed citations
8.
Islam, Rajib, Md. Rimon Parves, Abdulla Al Mamun, et al.. (2020). Cysteine focused covalent inhibitors against the main protease of SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 40(4). 1639–1658. 25 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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