Mohammad Saifur Rahman

865 total citations
46 papers, 520 citations indexed

About

Mohammad Saifur Rahman is a scholar working on Molecular Biology, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Mohammad Saifur Rahman has authored 46 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 7 papers in Electrical and Electronic Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Mohammad Saifur Rahman's work include Machine Learning in Bioinformatics (11 papers), RNA and protein synthesis mechanisms (10 papers) and Genomics and Phylogenetic Studies (9 papers). Mohammad Saifur Rahman is often cited by papers focused on Machine Learning in Bioinformatics (11 papers), RNA and protein synthesis mechanisms (10 papers) and Genomics and Phylogenetic Studies (9 papers). Mohammad Saifur Rahman collaborates with scholars based in Bangladesh, United States and Qatar. Mohammad Saifur Rahman's co-authors include M. Sohel Rahman, M. Kaykobad, Sanjay Saha, Swakkhar Shatabda, Md. Shamsuzzoha Bayzid, Md. Khaledur Rahman, Mamun Bin Ibne Reaz, Mohd Alauddin Mohd Ali, Nabil Ibtehaz and Mohammad Marufuzzaman and has published in prestigious journals such as Environmental Science & Technology, Bioinformatics and PLoS ONE.

In The Last Decade

Mohammad Saifur Rahman

41 papers receiving 508 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Saifur Rahman Bangladesh 12 295 56 55 50 27 46 520
Quang‐Thai Ho Taiwan 14 544 1.8× 49 0.9× 131 2.4× 16 0.3× 11 0.4× 18 794
Yingsheng Zhang China 13 205 0.7× 50 0.9× 34 0.6× 11 0.2× 33 1.2× 35 520
Zhixun Zhao China 12 160 0.5× 60 1.1× 61 1.1× 36 0.7× 21 0.8× 26 375
Quanzhong Liu China 11 473 1.6× 50 0.9× 53 1.0× 5 0.1× 14 0.5× 23 629
Qi Xuan China 15 60 0.2× 19 0.3× 79 1.4× 43 0.9× 23 0.9× 32 530
Hongyan Yan China 15 369 1.3× 36 0.6× 17 0.3× 35 0.7× 23 0.9× 43 870
Muhammad Tahir Pakistan 21 1.0k 3.5× 101 1.8× 202 3.7× 24 0.5× 6 0.2× 46 1.5k
Quan Chen China 14 295 1.0× 33 0.6× 46 0.8× 37 0.7× 111 4.1× 42 557
Dukka B. KC United States 11 213 0.7× 28 0.5× 78 1.4× 11 0.2× 37 1.4× 22 367
Federico Lecumberry Uruguay 10 68 0.2× 8 0.1× 34 0.6× 31 0.6× 13 0.5× 30 341

Countries citing papers authored by Mohammad Saifur Rahman

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Saifur Rahman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Saifur Rahman. 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 Mohammad Saifur Rahman. The network helps show where Mohammad Saifur Rahman may publish in the future.

Co-authorship network of co-authors of Mohammad Saifur Rahman

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Saifur Rahman. A scholar is included among the top collaborators of Mohammad Saifur Rahman 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 Mohammad Saifur Rahman. Mohammad Saifur Rahman 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.
Islam, Md. Saiful, Sangwu Lee, Wasifur Rahman, et al.. (2025). AI-Enabled Parkinson’s Disease Screening Using Smile Videos. NEJM AI. 2(7).
2.
Rahman, M. Sohel, et al.. (2025). Privacy-preserving customer churn prediction model in the context of telecommunication industry. Engineering Applications of Artificial Intelligence. 162. 112514–112514.
3.
Rahman, Mohammad Saifur, et al.. (2023). SAINT-Angle: self-attention augmented inception-inside-inception network and transfer learning improve protein backbone torsion angle prediction. Bioinformatics Advances. 3(1). vbad042–vbad042. 4 indexed citations
4.
Yang, Ning, Yuxuan Lin, Chih‐Piao Chuu, et al.. (2023). Ab Initio Computational Screening and Performance Assessment of van der Waals and Semimetallic Contacts to Monolayer WSe2P-Type Field-Effect Transistors. IEEE Transactions on Electron Devices. 70(4). 2090–2097. 18 indexed citations
5.
Samee, Md. Abul Hassan, et al.. (2023). ScribbleDom: using scribble-annotated histology images to identify domains in spatial transcriptomics data. Bioinformatics. 39(10). 6 indexed citations
6.
Kaykobad, M., et al.. (2023). NoVaTeST: identifying genes with location-dependent noise variance in spatial transcriptomics data. Bioinformatics. 39(6). 6 indexed citations
7.
Abedin, Mohammad Zoynul, et al.. (2022). A novel customer churn prediction model for the telecommunication industry using data transformation methods and feature selection. PLoS ONE. 17(12). e0278095–e0278095. 19 indexed citations
8.
Rahman, Mohammad Saifur, et al.. (2022). Succinylated lysine residue prediction revisited. Briefings in Bioinformatics. 24(1). 2 indexed citations
9.
Reaz, Rezwana, et al.. (2021). wQFM: highly accurate genome-scale species tree estimation from weighted quartets. Bioinformatics. 37(21). 3734–3743. 11 indexed citations
10.
Rahman, Mohammad Saifur, et al.. (2020). SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction. Bioinformatics. 36(17). 4599–4608. 57 indexed citations
11.
Rahman, Mohammad Saifur, et al.. (2020). ADACT: a tool for analysing (dis)similarity among nucleotide and protein sequences using minimal and relative absent words. Bioinformatics. 37(10). 1468–1470. 4 indexed citations
12.
Rahman, Mohammad Saifur, et al.. (2019). Antigenic: An improved prediction model of protective antigens. Artificial Intelligence in Medicine. 94. 28–41. 35 indexed citations
13.
Rahman, Mohammad Saifur, Swakkhar Shatabda, Sanjay Saha, M. Kaykobad, & M. Sohel Rahman. (2018). DPP-PseAAC: A DNA-binding protein prediction model using Chou’s general PseAAC. Journal of Theoretical Biology. 452. 22–34. 123 indexed citations
14.
Rahman, Mohammad Saifur, et al.. (2017). isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection. Artificial Intelligence in Medicine. 84. 90–100. 41 indexed citations
15.
Rahman, Mohammad Saifur, Md Yusuf Sarwar Uddin, M. Sohel Rahman, & M. Kaykobad. (2016). Using adaptive heartbeat rate on long-lived TCP connections. 1–9. 1 indexed citations
16.
17.
Rahman, Mohammad Saifur, et al.. (2014). Order preserving pattern matching revisited. Pattern Recognition Letters. 55. 15–21. 6 indexed citations
18.
Rahman, Mohammad Saifur, et al.. (2010). Antigenic detection of feline panleukopenia virus in local breed cats at Tangail district in Bangladesh. Murdoch Research Repository (Murdoch University). 6 indexed citations
19.
Rahman, Mohammad Saifur, et al.. (2006). Drawing lines by uniform packing. Computers & Graphics. 30(2). 207–212. 4 indexed citations
20.
Rahman, M. Sohel, M. Kaykobad, & Mohammad Saifur Rahman. (2005). A New Sufficient Condition for the Existence of Hamiltonian Paths.. Computers and Their Applications. 1(8320). 56–59. 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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