Eugene A. Rakhmatulin

786 total citations
8 papers, 568 citations indexed

About

Eugene A. Rakhmatulin is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Eugene A. Rakhmatulin has authored 8 papers receiving a total of 568 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 3 papers in Pharmacology. Recurrent topics in Eugene A. Rakhmatulin's work include Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (5 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Eugene A. Rakhmatulin is often cited by papers focused on Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (5 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Eugene A. Rakhmatulin collaborates with scholars based in United States and Russia. Eugene A. Rakhmatulin's co-authors include Tatiana Nikolskaya, Eugene Kirillov, Yuri Nikolsky, Andrej Bugrim, Sean Ekins, S. Yu. Sorokina, Richard Brennan, Kelly Li, Damir Dosymbekov and Raymond R. Samaha and has published in prestigious journals such as Journal of Alzheimer s Disease, Drug Metabolism and Disposition and BMC Biology.

In The Last Decade

Eugene A. Rakhmatulin

8 papers receiving 553 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eugene A. Rakhmatulin United States 8 350 154 91 51 49 8 568
Daniela Digles Austria 6 404 1.2× 128 0.8× 24 0.3× 43 0.8× 33 0.7× 13 618
Matthew Heindel United States 7 399 1.1× 103 0.7× 64 0.7× 33 0.6× 11 0.2× 8 590
Chris Black United States 12 396 1.1× 119 0.8× 194 2.1× 32 0.6× 15 0.3× 13 954
Rita Ciurlionis United States 10 641 1.8× 193 1.3× 122 1.3× 101 2.0× 22 0.4× 20 1.1k
Mark R. Southern United States 15 580 1.7× 90 0.6× 21 0.2× 36 0.7× 115 2.3× 19 776
Noriyuki Nakatsu Japan 15 660 1.9× 227 1.5× 123 1.4× 44 0.9× 15 0.3× 27 1.0k
David Moore United Kingdom 15 313 0.9× 53 0.3× 177 1.9× 166 3.3× 37 0.8× 29 748
Patricia W. Pan Canada 8 682 1.9× 34 0.2× 69 0.8× 67 1.3× 35 0.7× 9 936
Karl H. Clodfelter United States 7 338 1.0× 87 0.6× 61 0.7× 105 2.1× 8 0.2× 8 590
Stella O. Sieber United States 12 467 1.3× 99 0.6× 123 1.4× 29 0.6× 9 0.2× 17 731

Countries citing papers authored by Eugene A. Rakhmatulin

Since Specialization
Citations

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

Fields of papers citing papers by Eugene A. Rakhmatulin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eugene A. Rakhmatulin. 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 Eugene A. Rakhmatulin. The network helps show where Eugene A. Rakhmatulin may publish in the future.

Co-authorship network of co-authors of Eugene A. Rakhmatulin

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene A. Rakhmatulin. A scholar is included among the top collaborators of Eugene A. Rakhmatulin 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 Eugene A. Rakhmatulin. Eugene A. Rakhmatulin 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.
Nikolsky, Yuri, et al.. (2017). Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform. Methods in molecular biology. 1613. 101–124. 19 indexed citations
2.
Nikolsky, Yuri, et al.. (2009). Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform. Methods in molecular biology. 563. 177–196. 74 indexed citations
3.
Dezső, Zoltán, Yuri Nikolsky, Weiwei Shi, et al.. (2008). A comprehensive functional analysis of tissue specificity of human gene expression. BMC Biology. 6(1). 49–49. 156 indexed citations
4.
Ekins, Sean, Andrej Bugrim, Eugene Kirillov, et al.. (2006). Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms. Xenobiotica. 36(10-11). 877–901. 109 indexed citations
5.
Ekins, Sean, et al.. (2005). Computational prediction of human drug metabolism. Expert Opinion on Drug Metabolism & Toxicology. 1(2). 303–324. 64 indexed citations
6.
Ekins, Sean, Eugene Kirillov, Eugene A. Rakhmatulin, et al.. (2005). A COMBINED APPROACH TO DRUG METABOLISM AND TOXICITY ASSESSMENT. Drug Metabolism and Disposition. 34(3). 495–503. 85 indexed citations
7.
Soreghan, Brian A., Stefani N. Thomas, Karen Duff, et al.. (2005). Using proteomics and network analysis to elucidate the consequences of synaptic protein oxidation in a PS1+AβPP mouse model of Alzheimer's disease. Journal of Alzheimer s Disease. 8(3). 227–241. 20 indexed citations
8.
Ekins, Sean, Eugene Kirillov, Eugene A. Rakhmatulin, & Tatiana Nikolskaya. (2004). A NOVEL METHOD FOR VISUALIZING NUCLEAR HORMONE RECEPTOR NETWORKS RELEVANT TO DRUG METABOLISM. Drug Metabolism and Disposition. 33(3). 474–481. 41 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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