Ali Al‐Shahib

757 total citations
15 papers, 494 citations indexed

About

Ali Al‐Shahib is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health and Epidemiology. According to data from OpenAlex, Ali Al‐Shahib has authored 15 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Public Health, Environmental and Occupational Health and 4 papers in Epidemiology. Recurrent topics in Ali Al‐Shahib's work include Streptococcal Infections and Treatments (5 papers), Machine Learning in Bioinformatics (4 papers) and Bacterial Identification and Susceptibility Testing (4 papers). Ali Al‐Shahib is often cited by papers focused on Streptococcal Infections and Treatments (5 papers), Machine Learning in Bioinformatics (4 papers) and Bacterial Identification and Susceptibility Testing (4 papers). Ali Al‐Shahib collaborates with scholars based in United Kingdom, Netherlands and Maldives. Ali Al‐Shahib's co-authors include Rainer Breitling, David Gilbert, Anthony Underwood, Georgia Kapatai, Timothy G. Harrison, Norman K. Fry, David Litt, Carmen Sheppard, Janet Wilson and Stephanie Chisholm and has published in prestigious journals such as Journal of Clinical Microbiology, Emerging infectious diseases and BMC Bioinformatics.

In The Last Decade

Ali Al‐Shahib

15 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ali Al‐Shahib United Kingdom 11 159 139 127 119 93 15 494
Amelieke J. H. Cremers Netherlands 15 276 1.7× 70 0.5× 66 0.5× 104 0.9× 89 1.0× 31 462
Olivier Dubuis Switzerland 11 209 1.3× 116 0.8× 30 0.2× 67 0.6× 206 2.2× 14 490
Anirban Dutta India 12 89 0.6× 321 2.3× 60 0.5× 45 0.4× 95 1.0× 39 555
Marı́a del Mar Garcı́a-Suárez Spain 14 240 1.5× 194 1.4× 71 0.6× 99 0.8× 72 0.8× 31 594
Eric M. Ransom United States 13 111 0.7× 110 0.8× 42 0.3× 21 0.2× 203 2.2× 27 413
Irene Burckhardt Germany 14 229 1.4× 81 0.6× 67 0.5× 28 0.2× 78 0.8× 27 629
J.-J. Wu Taiwan 14 119 0.7× 233 1.7× 93 0.7× 64 0.5× 122 1.3× 24 608
Anthony R. Jones Thailand 11 49 0.3× 73 0.5× 65 0.5× 20 0.2× 126 1.4× 40 398
Farah Shahid Pakistan 17 165 1.0× 630 4.5× 53 0.4× 43 0.4× 232 2.5× 32 847
Ahalieyah Anantharajah Belgium 12 76 0.5× 246 1.8× 13 0.1× 43 0.4× 393 4.2× 23 746

Countries citing papers authored by Ali Al‐Shahib

Since Specialization
Citations

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

Fields of papers citing papers by Ali Al‐Shahib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali Al‐Shahib. 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 Ali Al‐Shahib. The network helps show where Ali Al‐Shahib may publish in the future.

Co-authorship network of co-authors of Ali Al‐Shahib

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

All Works

15 of 15 papers shown
1.
Coelho, J., Georgia Kapatai, Aleksey Jironkin, et al.. (2018). Genomic sequence investigation Streptococcus pyogenes clusters in England (2010–2015). Clinical Microbiology and Infection. 25(1). 96–101. 12 indexed citations
2.
Chalker, Victoria J., Aleksey Jironkin, Juliana Coelho, et al.. (2017). Genome analysis following a national increase in Scarlet Fever in England 2014. BMC Genomics. 18(1). 224–224. 47 indexed citations
3.
Afshar, Baharak, Claire E. Turner, Theresa Lamagni, et al.. (2017). Enhanced nasopharyngeal infection and shedding associated with an epidemic lineage of emm3 group A Streptococcus. Virulence. 8(7). 1390–1400. 12 indexed citations
4.
Chalker, Victoria J., Alyson Smith, Ali Al‐Shahib, et al.. (2016). Integration of Genomic and Other Epidemiologic Data to Investigate and Control a Cross-Institutional Outbreak ofStreptococcus pyogenes. Emerging infectious diseases. 22(6). 973–980. 16 indexed citations
5.
Kapatai, Georgia, Carmen Sheppard, Ali Al‐Shahib, et al.. (2016). Whole genome sequencing of Streptococcus pneumoniae : development, evaluation and verification of targets for serogroup and serotype prediction using an automated pipeline. PeerJ. 4. e2477–e2477. 118 indexed citations
6.
Chalker, Victoria J., Alyson Smith, Ali Al‐Shahib, et al.. (2016). Integration of Genomic and Other Epidemiologic Data to Investigate and Control a Cross-Institutional Outbreak ofStreptococcus pyogenes. Emerging infectious diseases. 22(6). 973–980. 1 indexed citations
7.
Chisholm, Stephanie, Janet Wilson, Sarah Alexander, et al.. (2015). An outbreak of high-level azithromycin resistantNeisseria gonorrhoeaein England. Sexually Transmitted Infections. 92(5). 365–367. 73 indexed citations
8.
Turton, Jane F., Laura Wright, Anthony Underwood, et al.. (2015). High-Resolution Analysis by Whole-Genome Sequencing of an International Lineage (Sequence Type 111) of Pseudomonas aeruginosa Associated with Metallo-Carbapenemases in the United Kingdom. Journal of Clinical Microbiology. 53(8). 2622–2631. 45 indexed citations
9.
Al‐Shahib, Ali & Anthony Underwood. (2013). snp-search: simple processing, manipulation and searching of SNPs from high-throughput sequencing. BMC Bioinformatics. 14(1). 326–326. 4 indexed citations
10.
Shah, Haroun N., Graham Ball, Raju Misra, et al.. (2011). Tracing the transition of methicillin resistance in sub-populations of Staphylococcus aureus, using SELDI-TOF Mass Spectrometry and Artificial Neural Network Analysis. Systematic and Applied Microbiology. 34(1). 81–86. 23 indexed citations
11.
Al‐Shahib, Ali, et al.. (2010). Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics. BMC Bioinformatics. 11(1). 437–437. 9 indexed citations
12.
Al‐Shahib, Ali, Rainer Breitling, & David Gilbert. (2007). Predicting protein function by machine learning on amino acid sequences – a critical evaluation. BMC Genomics. 8(1). 78–78. 26 indexed citations
13.
Al‐Shahib, Ali, Rainer Breitling, & David Gilbert. (2005). Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence. PubMed. 4(3). 195–203. 84 indexed citations
14.
Al‐Shahib, Ali, Rainer Breitling, & David Gilbert. (2005). Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence. Research Explorer (The University of Manchester). 4(3). 195–203. 4 indexed citations
15.
Al‐Shahib, Ali, Rainer Breitling, & David Gilbert. (2005). FRANKSUM: NEW FEATURE SELECTION METHOD FOR PROTEIN FUNCTION PREDICTION. International Journal of Neural Systems. 15(4). 259–275. 20 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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