Ramzan Umarov

1.3k total citations
12 papers, 716 citations indexed

About

Ramzan Umarov is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pollution. According to data from OpenAlex, Ramzan Umarov has authored 12 papers receiving a total of 716 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 1 paper in Pollution. Recurrent topics in Ramzan Umarov's work include RNA and protein synthesis mechanisms (7 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (4 papers). Ramzan Umarov is often cited by papers focused on RNA and protein synthesis mechanisms (7 papers), Genomics and Phylogenetic Studies (5 papers) and Machine Learning in Bioinformatics (4 papers). Ramzan Umarov collaborates with scholars based in Saudi Arabia, United States and Hong Kong. Ramzan Umarov's co-authors include Victor Solovyev, Yu Li, Xin Gao, Lihua Li, Ming Fan, Ilham A. Shahmuradov, Bingqing Xie, Sheng Wang, Hiroyuki Kuwahara and Le Song and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Ramzan Umarov

12 papers receiving 704 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ramzan Umarov Saudi Arabia	9	589	80	68	35	34	12	716
Jongwan Kim South Korea	13	246 0.4×	60 0.8×	57 0.8×	7 0.2×	37 1.1×	38	504
Achraf El Allali Morocco	16	276 0.5×	100 1.3×	154 2.3×	12 0.3×	31 0.9×	62	641
Pawan Kumar India	9	339 0.6×	108 1.4×	39 0.6×	15 0.4×	30 0.9×	57	647
Meenu Sharma India	7	607 1.0×	70 0.9×	35 0.5×	11 0.3×	35 1.0×	20	800
Philippe Marc France	13	676 1.1×	60 0.8×	78 1.1×	21 0.6×	11 0.3×	18	864
Robert Rentzsch United Kingdom	12	768 1.3×	115 1.4×	59 0.9×	12 0.3×	75 2.2×	13	894
Bhusan K. Kuntal India	8	311 0.5×	37 0.5×	52 0.8×	7 0.2×	54 1.6×	19	461
Amer H. Asseri Saudi Arabia	12	193 0.3×	45 0.6×	24 0.4×	24 0.7×	14 0.4×	34	441
Xiaoxue Chen China	13	388 0.7×	98 1.2×	43 0.6×	7 0.2×	93 2.7×	28	976
Bryce Kille United States	11	462 0.8×	19 0.2×	44 0.6×	7 0.2×	31 0.9×	16	583

Countries citing papers authored by Ramzan Umarov

Since Specialization

Citations

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

Fields of papers citing papers by Ramzan Umarov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ramzan Umarov

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

Umarov, Ramzan, et al.. (2021). ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation. PLoS Computational Biology. 17(9). e1009376–e1009376. 6 indexed citations

Li, Yu, Zeling Xu, Wenkai Han, et al.. (2021). HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes. Microbiome. 9(1). 40–40. 70 indexed citations

Umarov, Ramzan, Yu Li, & Erik Arner. (2021). DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment. PLoS Computational Biology. 17(10). e1009465–e1009465. 8 indexed citations

Li, Yu, et al.. (2020). RNA Secondary Structure Prediction By Learning Unrolled Algorithms. arXiv (Cornell University). 9 indexed citations

Lam, Jordy Homing, Yu Li, Lizhe Zhu, et al.. (2019). A deep learning framework to predict binding preference of RNA constituents on protein surface. Nature Communications. 10(1). 4941–4941. 87 indexed citations

Umarov, Ramzan, Hiroyuki Kuwahara, Yu Li, Xin Gao, & Victor Solovyev. (2018). Promoter analysis and prediction in the human genome using sequence-based deep learning models. Bioinformatics. 35(16). 2730–2737. 74 indexed citations

Umarov, Ramzan & Victor Solovyev. (2017). Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks. PLoS ONE. 12(2). e0171410–e0171410. 158 indexed citations

Shahmuradov, Ilham A., Ramzan Umarov, & Victor Solovyev. (2017). TSSPlant: a new tool for prediction of plant Pol II promoters. Nucleic Acids Research. 45(8). gkw1353–gkw1353. 82 indexed citations

Li, Yu, Sheng Wang, Ramzan Umarov, et al.. (2017). DEEPre: sequence-based enzyme EC number prediction by deep learning. Bioinformatics. 34(5). 760–769. 183 indexed citations

10.

Kuwahara, Hiroyuki, Xuefeng Cui, Ramzan Umarov, et al.. (2017). SBOLme: a Repository of SBOL Parts for Metabolic Engineering. ACS Synthetic Biology. 6(4). 732–736. 5 indexed citations

11.

Kuwahara, Hiroyuki, et al.. (2017). ACRE: Absolute concentration robustness exploration in module-based combinatorial networks. PubMed. 2(1). ysx001–ysx001. 2 indexed citations

12.

Dai, Hanjun, Ramzan Umarov, Hiroyuki Kuwahara, et al.. (2017). Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape. Bioinformatics. 33(22). 3575–3583. 32 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.

Explore authors with similar magnitude of impact