Murtada K. Elbashir

53 total papers · 653 total citations
45 papers, 356 citations indexed

About

Murtada K. Elbashir is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Murtada K. Elbashir has authored 45 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 12 papers in Artificial Intelligence and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Murtada K. Elbashir's work include Gene expression and cancer classification (8 papers), Machine Learning in Bioinformatics (8 papers) and RNA and protein synthesis mechanisms (5 papers). Murtada K. Elbashir is often cited by papers focused on Gene expression and cancer classification (8 papers), Machine Learning in Bioinformatics (8 papers) and RNA and protein synthesis mechanisms (5 papers). Murtada K. Elbashir collaborates with scholars based in Saudi Arabia, Sudan and South Africa. Murtada K. Elbashir's co-authors include Mohanad Mohammed, Henry Mwambi, Bernard Omolo, Innocent B. Mboya, Mohamed Ezz, Mohamed Elhafiz Mustafa, Jianxin Wang, Jamshaid Ul Rahman, Waseem Asghar Khan and Umer Farooq and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Murtada K. Elbashir

39 papers receiving 337 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Murtada K. Elbashir	120	119	56	43	33	45	356
Wei Li	66 0.6×	153 1.3×	42 0.8×	38 0.9×	53 1.6×	18	387
Dongyuan Li	117 1.0×	67 0.6×	22 0.4×	75 1.7×	21 0.6×	47	365
Marco Frasca	102 0.8×	185 1.6×	51 0.9×	41 1.0×	22 0.7×	31	364
Masayuki Kobayashi	75 0.6×	39 0.3×	25 0.4×	38 0.9×	19 0.6×	35	309
Qiuyang Liu	68 0.6×	43 0.4×	22 0.4×	80 1.9×	19 0.6×	31	348
Xiaoli Zhou	80 0.7×	37 0.3×	104 1.9×	64 1.5×	6 0.2×	40	349
R.C. Mann	127 1.1×	64 0.5×	17 0.3×	113 2.6×	9 0.3×	27	368
Xingye Qiao	120 1.0×	76 0.6×	19 0.3×	84 2.0×	7 0.2×	32	339
Xuebing Yang	194 1.6×	23 0.2×	38 0.7×	113 2.6×	16 0.5×	38	369
Asghar Ali Shah	92 0.8×	80 0.7×	92 1.6×	47 1.1×	10 0.3×	46	392

Countries citing papers authored by Murtada K. Elbashir

Since Specialization

Citations

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

Fields of papers citing papers by Murtada K. Elbashir

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Murtada K. Elbashir. 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 Murtada K. Elbashir. The network helps show where Murtada K. Elbashir may publish in the future.

Co-authorship network of co-authors of Murtada K. Elbashir

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

All Works

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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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