Miah Roney

403 total citations
56 papers, 226 citations indexed

About

Miah Roney is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Miah Roney has authored 56 papers receiving a total of 226 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 17 papers in Computational Theory and Mathematics and 10 papers in Organic Chemistry. Recurrent topics in Miah Roney's work include Computational Drug Discovery Methods (17 papers), Synthesis and biological activity (7 papers) and Natural Antidiabetic Agents Studies (6 papers). Miah Roney is often cited by papers focused on Computational Drug Discovery Methods (17 papers), Synthesis and biological activity (7 papers) and Natural Antidiabetic Agents Studies (6 papers). Miah Roney collaborates with scholars based in Malaysia, Bangladesh and India. Miah Roney's co-authors include Mohd Fadhlizil Fasihi Mohd Aluwi, Saıful Nizam Tajuddin, Kamal Rullah, Amit Dubey, Abdul Rashid Issahaku, Syahrul Imran, Md. Nazim Uddin, Aisha Tufail, Md. Sanower Hossain and Hazrulrizawati Abd Hamid and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Phytotherapy Research.

In The Last Decade

Miah Roney

46 papers receiving 223 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miah Roney Malaysia 9 73 51 50 31 26 56 226
Toheeb A. Balogun Nigeria 10 87 1.2× 71 1.4× 53 1.1× 16 0.5× 33 1.3× 26 247
Dhrubo Ahmed Khan Bangladesh 6 101 1.4× 65 1.3× 24 0.5× 31 1.0× 39 1.5× 10 258
Abdul Rashid Issahaku South Africa 9 150 2.1× 112 2.2× 61 1.2× 20 0.6× 25 1.0× 36 304
Ahmad Alzamami Saudi Arabia 12 158 2.2× 67 1.3× 83 1.7× 13 0.4× 24 0.9× 24 347
Tamina Park South Korea 9 93 1.3× 34 0.7× 51 1.0× 9 0.3× 25 1.0× 16 287
Xolani Henry Makhoba South Africa 7 149 2.0× 66 1.3× 62 1.2× 16 0.5× 11 0.4× 14 275
Umesh D. Laddha India 10 64 0.9× 33 0.6× 23 0.5× 14 0.5× 20 0.8× 24 294
Ashish Wadhwani India 11 131 1.8× 45 0.9× 75 1.5× 22 0.7× 72 2.8× 30 391
Pedro Fong Macao 10 152 2.1× 55 1.1× 30 0.6× 12 0.4× 34 1.3× 24 334
Njogu M. Kimani Kenya 10 129 1.8× 72 1.4× 58 1.2× 38 1.2× 60 2.3× 35 311

Countries citing papers authored by Miah Roney

Since Specialization
Citations

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

Fields of papers citing papers by Miah Roney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miah Roney

This figure shows the co-authorship network connecting the top 25 collaborators of Miah Roney. A scholar is included among the top collaborators of Miah Roney 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 Miah Roney. Miah Roney 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.
Roney, Miah, Md. Nazim Uddin, Azmat Ali Khan, et al.. (2025). Repurposing of dipeptidyl peptidase FDA-approved drugs in Alzheimer’s disease using network pharmacology and in-silico approaches. Computational Biology and Chemistry. 116. 108378–108378. 2 indexed citations
2.
Uddin, Md. Nazim, et al.. (2025). Exploring the anti-cancer potential of daidzin in breast cancer: Integrated bioinformatics and computational insights on oncogene inhibition. Computational Biology and Chemistry. 119. 108590–108590.
3.
Roney, Miah, Abdul Rashid Issahaku, Azmat Ali Khan, et al.. (2025). In Silico Evaluation of Approved Drug Library to Discover Tyrosine Threonine Kinase Inhibitors for Colon Cancer. ChemistrySelect. 10(17). 1 indexed citations
6.
Roney, Miah, Abdul Rashid Issahaku, Amit Dubey, et al.. (2025). In-silico evaluation of diffractaic acid as novel anti-diabetic inhibitor against dipeptidyl peptidase IV enzyme. In Silico Pharmacology. 13(1). 24–24. 2 indexed citations
7.
Roney, Miah & Mohd Fadhlizil Fasihi Mohd Aluwi. (2024). Computational studies demonstrating dithymoquinone of Nigella sativa as a potential anti-dengue agent: Short review. SHILAP Revista de lepidopterología. 2(3). 335–338.
9.
Roney, Miah, Md. Nazim Uddin, Kamal Rullah, et al.. (2024). Design, synthesis, structural characterization, cytotoxicity and computational studies of Usnic acid derivative as potential anti-breast cancer agent against MCF7 and T47D cell lines. Computational Biology and Chemistry. 115. 108303–108303. 1 indexed citations
10.
Roney, Miah, Abdul Rashid Issahaku, Md. Nazim Uddin, Anke Wilhelm, & Mohd Fadhlizil Fasihi Mohd Aluwi. (2024). Exploration of leads from bis-indole based triazine derivatives targeting human aldose reductase in diabetic type 2: in-silico approaches. 3 Biotech. 15(1). 5–5.
11.
Roney, Miah & Mohd Fadhlizil Fasihi Mohd Aluwi. (2024). Evolution of SARS-CoV-2 from BA.2.86 to JN.1 variations and detection in Bangladesh. SHILAP Revista de lepidopterología. 48(1). 1 indexed citations
12.
Roney, Miah, et al.. (2023). Inhibitory effect of Sinapic acid derivatives targeting structural and non-structural proteins of dengue virus serotype 2: An in-silico assessment. SHILAP Revista de lepidopterología. 2. 100028–100028. 3 indexed citations
13.
Roney, Miah, et al.. (2023). Diabetic wound healing of aloe vera major phytoconstituents through TGF-β1 suppression via in-silico docking, molecular dynamic simulation and pharmacokinetic studies. Journal of Biomolecular Structure and Dynamics. 42(24). 13939–13952. 3 indexed citations
14.
Roney, Miah, et al.. (2023). Polypharmacological assessment of Amoxicillin and its analogues against the bacterial DNA gyrase B using molecular docking, DFT and molecular dynamics simulation. SHILAP Revista de lepidopterología. 2. 100024–100024. 4 indexed citations
16.
Roney, Miah, et al.. (2023). Computer-aided anti-cancer drug discovery of EGFR protein based on virtual screening of drug bank, ADMET, docking, DFT and molecular dynamic simulation studies. Journal of Biomolecular Structure and Dynamics. 42(18). 9662–9677. 4 indexed citations
17.
Roney, Miah, et al.. (2023). Pharmacophore-based Molecular Docking of Usnic Acid Derivatives to Discover Anti-viral drugs Against Influenza A Virus. Journal of Research in Pharmacy. 27(3)(27(3)). 1021–1038. 2 indexed citations
18.
Roney, Miah, Abdul Rashid Issahaku, & Mohd Fadhlizil Fasihi Mohd Aluwi. (2023). Virtual screening of pyrazole derivatives of usnic acid as new class of anti-hyperglycemic agents against PPARγ agonists. In Silico Pharmacology. 11(1). 36–36.
19.
Rullah, Kamal, Miah Roney, Nur Farisya Shamsudin, et al.. (2022). Identification of Novel 5-Lipoxygenase-Activating Protein (FLAP) Inhibitors by an Integrated Method of Pharmacophore Virtual Screening, Docking, QSAR and ADMET Analyses. Journal of Computational Biophysics and Chemistry. 22(1). 77–97. 8 indexed citations
20.
Roney, Miah, Md. Sanower Hossain, & Mohd Fadhlizil Fasihi Mohd Aluwi. (2022). In silico Analysis for Discovery of Dengue Virus Inhibitor from Natural Compounds. 3. 2 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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