Salma Jamal

1.5k total citations
64 papers, 1.1k citations indexed

About

Salma Jamal is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Salma Jamal has authored 64 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 25 papers in Computational Theory and Mathematics and 19 papers in Infectious Diseases. Recurrent topics in Salma Jamal's work include Computational Drug Discovery Methods (25 papers), Tuberculosis Research and Epidemiology (16 papers) and Cancer therapeutics and mechanisms (14 papers). Salma Jamal is often cited by papers focused on Computational Drug Discovery Methods (25 papers), Tuberculosis Research and Epidemiology (16 papers) and Cancer therapeutics and mechanisms (14 papers). Salma Jamal collaborates with scholars based in India, Egypt and Canada. Salma Jamal's co-authors include Abhinav Grover, Sukriti Goyal, Sonam Grover, Aditi Singh, Vinod Scaria, Asheesh Shanker, Chetna Tyagi, Sharad Verma, Vinita Periwal and Seyed E. Hasnain and has published in prestigious journals such as PLoS ONE, Scientific Reports and Frontiers in Immunology.

In The Last Decade

Salma Jamal

63 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Salma Jamal India 20 663 307 243 92 79 64 1.1k
Tina Ritschel Netherlands 20 627 0.9× 223 0.7× 183 0.8× 145 1.6× 89 1.1× 32 1.1k
Thomas R. Lane United States 22 549 0.8× 572 1.9× 285 1.2× 109 1.2× 86 1.1× 68 1.5k
Michael Hsing Canada 19 950 1.4× 600 2.0× 266 1.1× 82 0.9× 71 0.9× 35 1.6k
Shan Chang China 21 1.1k 1.6× 374 1.2× 140 0.6× 87 0.9× 101 1.3× 92 1.6k
Sumra Wajid Abbasi Pakistan 18 584 0.9× 313 1.0× 261 1.1× 110 1.2× 66 0.8× 63 1.2k
Foysal Ahammad Saudi Arabia 19 589 0.9× 370 1.2× 166 0.7× 59 0.6× 141 1.8× 40 1.1k
Kimberley M. Zorn United States 22 516 0.8× 672 2.2× 247 1.0× 114 1.2× 117 1.5× 36 1.5k
Özlem Taştan Bishop South Africa 23 1.2k 1.8× 521 1.7× 297 1.2× 107 1.2× 72 0.9× 100 1.7k
Ana C. Puhl United States 16 494 0.7× 378 1.2× 141 0.6× 50 0.5× 50 0.6× 48 1.0k
Woong‐Hee Shin South Korea 18 756 1.1× 455 1.5× 108 0.4× 76 0.8× 52 0.7× 43 1.1k

Countries citing papers authored by Salma Jamal

Since Specialization
Citations

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

Fields of papers citing papers by Salma Jamal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salma Jamal

This figure shows the co-authorship network connecting the top 25 collaborators of Salma Jamal. A scholar is included among the top collaborators of Salma Jamal 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 Salma Jamal. Salma Jamal 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.
Singh, Digvijay, et al.. (2024). Identification and characterization of repurposed small molecule inhibitors of Mycobacterium tuberculosis caseinolytic protease B (ClpB) as anti-mycobacterials. International Journal of Biological Macromolecules. 264(Pt 1). 130614–130614.
2.
Jamal, Salma, Rahul Sharma, Zahoor Ahmad, et al.. (2024). Revitalizing antimicrobial strategies: paromomycin and dicoumarol repurposed as potent inhibitors of M.tb's replication machinery via targeting the vital protein DnaN. International Journal of Biological Macromolecules. 278(Pt 3). 134652–134652. 1 indexed citations
3.
Jamal, Salma, et al.. (2023). Unravelling the potential of Triflusal as an anti-TB repurposed drug by targeting replication protein DciA. Microbes and Infection. 26(3). 105284–105284. 4 indexed citations
4.
5.
Srivastava, Ankit, et al.. (2022). Molecular insights into the critical role of gallate moiety of green tea catechins in modulating prion fibrillation, cellular internalization, and neuronal toxicity. International Journal of Biological Macromolecules. 223(Pt A). 755–765. 8 indexed citations
6.
Sharma, Rahul, Vikrant Singh Rajput, Salma Jamal, Abhinav Grover, & Sonam Grover. (2021). Author Correction: An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins. Scientific Reports. 11(1). 16844–16844. 2 indexed citations
7.
Sharma, Rahul, Vikrant Singh Rajput, Salma Jamal, Abhinav Grover, & Sonam Grover. (2021). An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins. Scientific Reports. 11(1). 13836–13836. 39 indexed citations
8.
Jamal, Salma, et al.. (2020). Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis. Scientific Reports. 10(1). 5487–5487. 58 indexed citations
9.
Singh, Hina, Mohd Khubaib, Salma Jamal, et al.. (2020). Mapping the genomic landscape & diversity of COVID-19 based on >3950 clinical isolates of SARS-CoV-2. The Indian Journal of Medical Research. 151(5). 474–478. 13 indexed citations
10.
Jamal, Salma, Abhinav Grover, & Sonam Grover. (2019). Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer’s Disease. Frontiers in Pharmacology. 10. 780–780. 46 indexed citations
11.
Jamal, Salma, et al.. (2019). Computational models for the prediction of adverse cardiovascular drug reactions. Journal of Translational Medicine. 17(1). 171–171. 30 indexed citations
12.
Goyal, Sukriti, et al.. (2017). GQSAR modeling and combinatorial library generation of 4-phenylquinazoline-2-carboxamide derivatives as antiproliferative agents in human Glioblastoma tumors. Computational Biology and Chemistry. 69. 147–152. 2 indexed citations
13.
Jamal, Salma, Sukriti Goyal, Asheesh Shanker, & Abhinav Grover. (2016). Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes. BMC Genomics. 17(1). 807–807. 31 indexed citations
14.
Verma, Sharad, Sonam Grover, Chetna Tyagi, et al.. (2016). Hydrophobic Interactions Are a Key to MDM2 Inhibition by Polyphenols as Revealed by Molecular Dynamics Simulations and MM/PBSA Free Energy Calculations. PLoS ONE. 11(2). e0149014–e0149014. 77 indexed citations
15.
Goyal, Sukriti, et al.. (2016). Molecular modeling and lead design of substituted zanamivir derivatives as potent anti-influenza drugs. BMC Bioinformatics. 17(S19). 512–512. 6 indexed citations
16.
Gupta, Ankita, et al.. (2015). Abrogation of AuroraA-TPX2 by novel natural inhibitors: molecular dynamics-based mechanistic analysis. Journal of Receptors and Signal Transduction. 35(6). 626–633. 9 indexed citations
17.
Jain, Ritu, et al.. (2015). Resisting the Resistance in Cancer: Cheminformatics Studies on Short- Path Base Excision Repair Pathway Antagonists Using Supervised Learning Approaches. Combinatorial Chemistry & High Throughput Screening. 18(9). 881–891. 4 indexed citations
18.
19.
Tyagi, Chetna, et al.. (2015). Identification of chebulinic acid as potent natural inhibitor of M. tuberculosis DNA gyrase and molecular insights into its binding mode of action. Computational Biology and Chemistry. 59. 37–47. 35 indexed citations
20.
Jamal, Salma & Vinod Scaria. (2013). Cheminformatic models based on machine learning for pyruvate kinase inhibitors of Leishmania mexicana. BMC Bioinformatics. 14(1). 329–329. 30 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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