Rayees Rahman

604 total citations
16 papers, 291 citations indexed

About

Rayees Rahman is a scholar working on Molecular Biology, Pharmacology and Computational Theory and Mathematics. According to data from OpenAlex, Rayees Rahman has authored 16 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Pharmacology and 6 papers in Computational Theory and Mathematics. Recurrent topics in Rayees Rahman's work include Computational Drug Discovery Methods (6 papers), Microbial Natural Products and Biosynthesis (5 papers) and Bioinformatics and Genomic Networks (5 papers). Rayees Rahman is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Microbial Natural Products and Biosynthesis (5 papers) and Bioinformatics and Genomic Networks (5 papers). Rayees Rahman collaborates with scholars based in United States, Israel and Sweden. Rayees Rahman's co-authors include Avner Schlessinger, Peter M.U. Ung, Balaguru Ravikumar, Anna Cichońska, Stephen Z. Levine, Abraham Reichenberg, Sven Sandin, Arad Kodesh, Weigang Qiu and Jinyuan Yan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Rayees Rahman

16 papers receiving 273 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rayees Rahman United States	10	173	60	37	26	23	16	291
Qingning Yuan China	12	347 2.0×	43 0.7×	7 0.2×	8 0.3×	15 0.7×	23	517
Karen Stefanisko United States	10	327 1.9×	23 0.4×	6 0.2×	31 1.2×	28 1.2×	12	512
Zhihong Ke China	11	157 0.9×	9 0.1×	37 1.0×	36 1.4×	16 0.7×	31	326
Apoorva Mandavilli United States	10	121 0.7×	13 0.2×	31 0.8×	6 0.2×	20 0.9×	48	368
Damir Bojadzic United States	8	104 0.6×	76 1.3×	5 0.1×	8 0.3×	11 0.5×	8	299
Jennifer Liddle United States	8	148 0.9×	14 0.2×	5 0.1×	18 0.7×	12 0.5×	13	216
Maotian Zhou China	9	344 2.0×	16 0.3×	7 0.2×	7 0.3×	16 0.7×	15	563
Karen Rutherford United States	11	294 1.7×	22 0.4×	8 0.2×	32 1.2×	24 1.0×	12	405
Britton Boras United States	7	117 0.7×	47 0.8×	4 0.1×	6 0.2×	26 1.1×	12	279
Nanda G. Aduri Denmark	10	259 1.5×	13 0.2×	4 0.1×	28 1.1×	16 0.7×	16	450

Countries citing papers authored by Rayees Rahman

Since Specialization

Citations

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

Fields of papers citing papers by Rayees Rahman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rayees Rahman

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

All Works

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16 of 16 papers shown

Cichońska, Anna, Balaguru Ravikumar, & Rayees Rahman. (2024). AI for targeted polypharmacology: The next frontier in drug discovery. Current Opinion in Structural Biology. 84. 102771–102771. 27 indexed citations

Ravikumar, Balaguru, et al.. (2024). Leveraging multiple data types for improved compound-kinase bioactivity prediction. Nature Communications. 15(1). 7596–7596. 3 indexed citations

Trozzi, Francesco, et al.. (2023). Investigating the conformational landscape of AlphaFold2-predicted protein kinase structures. Bioinformatics Advances. 3(1). vbad129–vbad129. 13 indexed citations

Stein, David, et al.. (2022). Structural signatures: a web server for exploring a database of and generating protein structural features from human cell lines and tissues. Database. 2022. 1 indexed citations

Rahman, Rayees, Jens Hansen, Yuguang Xiong, et al.. (2021). Protein structure–based gene expression signatures. Proceedings of the National Academy of Sciences. 118(19). 5 indexed citations

Kodesh, Arad, Stephen Z. Levine, Vahe Khachadourian, et al.. (2021). Maternal health around pregnancy and autism risk: a diagnosis-wide, population-based study. Psychological Medicine. 52(16). 4076–4084. 9 indexed citations

Stein, David, et al.. (2021). Structural Signatures (sGES): A Web Tool for Enriching Gene Expression Signatures With Protein Structural Features. SSRN Electronic Journal. 1 indexed citations

Hasselt, J. G. Coen van, Rayees Rahman, Jens Hansen, et al.. (2020). Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity. Nature Communications. 11(1). 4809–4809. 28 indexed citations

Rahman, Rayees, Arad Kodesh, Stephen Z. Levine, et al.. (2020). Identification of newborns at risk for autism using electronic medical records and machine learning. European Psychiatry. 63(1). e22–e22. 33 indexed citations

10.

Yan, Jinyuan, Chen Liao, Wook Kim, et al.. (2019). Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection. PLoS Computational Biology. 15(12). e1007562–e1007562. 14 indexed citations

11.

Ung, Peter M.U., Rayees Rahman, & Avner Schlessinger. (2019). Redefining the Protein Kinase Conformational Space with Machine Learning. Biophysical Journal. 116(3). 58a–59a. 1 indexed citations

12.

Ung, Peter M.U., Rayees Rahman, & Avner Schlessinger. (2018). Redefining the Protein Kinase Conformational Space with Machine Learning. Cell chemical biology. 25(7). 916–924.e2. 66 indexed citations

13.

Janecka, Magdalena, Arad Kodesh, Stephen Z. Levine, et al.. (2018). Association of Autism Spectrum Disorder With Prenatal Exposure to Medication Affecting Neurotransmitter Systems. JAMA Psychiatry. 75(12). 1217–1217. 24 indexed citations

14.

Rahman, Rayees, Peter M.U. Ung, & Avner Schlessinger. (2018). KinaMetrix: a web resource to investigate kinase conformations and inhibitor space. Nucleic Acids Research. 47(D1). D361–D366. 20 indexed citations

15.

Heimann, Andrea S., Achla Gupta, Ivone Gomes, et al.. (2017). Generation of G protein-coupled receptor antibodies differentially sensitive to conformational states. PLoS ONE. 12(11). e0187306–e0187306. 9 indexed citations

16.

Yan, Jinyuan, Maxime Déforet, Rayees Rahman, et al.. (2017). Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network. PLoS Computational Biology. 13(8). e1005677–e1005677. 37 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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