Qurrat Ul Ain

1.1k total citations
28 papers, 584 citations indexed

About

Qurrat Ul Ain is a scholar working on Oncology, Molecular Biology and Cell Biology. According to data from OpenAlex, Qurrat Ul Ain has authored 28 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 7 papers in Molecular Biology and 7 papers in Cell Biology. Recurrent topics in Qurrat Ul Ain's work include Cutaneous Melanoma Detection and Management (9 papers), melanin and skin pigmentation (7 papers) and Computational Drug Discovery Methods (4 papers). Qurrat Ul Ain is often cited by papers focused on Cutaneous Melanoma Detection and Management (9 papers), melanin and skin pigmentation (7 papers) and Computational Drug Discovery Methods (4 papers). Qurrat Ul Ain collaborates with scholars based in New Zealand, Pakistan and United Kingdom. Qurrat Ul Ain's co-authors include Antoniya A. Aleksandrova, Pedro J. Ballester, Mengjie Zhang, Harith Al-Sahaf, Bing Xue, Andreas Bender, Isidro Cortés‐Ciriano, Thérèse E. Malliavin, Oscar Méndez‐Lucio and Gerard J. P. van Westen and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Cybernetics and International Communications in Heat and Mass Transfer.

In The Last Decade

Qurrat Ul Ain

22 papers receiving 572 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qurrat Ul Ain New Zealand 10 308 305 113 76 65 28 584
Xiaolong Wu China 15 236 0.8× 249 0.8× 174 1.5× 33 0.4× 60 0.9× 39 710
Qing Ye China 10 182 0.6× 195 0.6× 62 0.5× 45 0.6× 57 0.9× 45 448
Fahimeh Ghasemi Iran 10 206 0.7× 177 0.6× 104 0.9× 42 0.6× 68 1.0× 23 472
Ruihan Yang China 9 344 1.1× 335 1.1× 126 1.1× 49 0.6× 62 1.0× 31 610
Ch. Madhu Babu India 5 224 0.7× 196 0.6× 84 0.7× 56 0.7× 26 0.4× 15 446
Simon Johansson Sweden 8 487 1.6× 330 1.1× 404 3.6× 59 0.8× 69 1.1× 19 678
Ryan Byrne Switzerland 4 382 1.2× 331 1.1× 193 1.7× 38 0.5× 51 0.8× 8 692
Karim Abbasi Iran 15 446 1.4× 455 1.5× 180 1.6× 108 1.4× 16 0.2× 21 722
Jannis Born Switzerland 15 272 0.9× 316 1.0× 166 1.5× 133 1.8× 41 0.6× 25 744
Yuemin Bian United States 11 280 0.9× 298 1.0× 106 0.9× 28 0.4× 25 0.4× 19 535

Countries citing papers authored by Qurrat Ul Ain

Since Specialization
Citations

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

Fields of papers citing papers by Qurrat Ul Ain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qurrat Ul Ain. 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 Qurrat Ul Ain. The network helps show where Qurrat Ul Ain may publish in the future.

Co-authorship network of co-authors of Qurrat Ul Ain

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

All Works

20 of 20 papers shown
1.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2025). Genetic Programming for Malignancy Diagnosis From Breast Cancer Histopathological Images: A Feature Learning Approach. IEEE Transactions on Emerging Topics in Computational Intelligence. 10(2). 1123–1136.
2.
Ain, Qurrat Ul, et al.. (2025). Rapid onset of neurological symptoms in an HIV-positive patient with progressive multifocal leukoencephalopathy: a case report. Annals of Medicine and Surgery. 87(6). 3994–3998.
3.
4.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2024). Automatically Evolving Interpretable Feature Vectors Using Genetic Programming for an Ensemble Classifier in Skin Cancer Detection. IEEE Computational Intelligence Magazine. 19(3). 26–41.
5.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2024). Exploring Genetic Programming Models in Computer-Aided Diagnosis of Skin Cancer Images. 4. 1–8. 1 indexed citations
6.
Ain, Qurrat Ul, Ayesha Malik, Imran Shahid, et al.. (2024). Exploring antiviral activity of Betanin and Glycine Betaine against dengue virus type-2 in transfected Hela cells. Microbial Pathogenesis. 195. 106894–106894. 1 indexed citations
7.
Ain, Qurrat Ul, et al.. (2024). Enhanced heat transfer in novel star-shaped enclosure with hybrid nanofluids: A neural network-assisted study. Case Studies in Thermal Engineering. 61. 105065–105065. 4 indexed citations
8.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2024). Feature Extraction with Automated Scale Selection in Skin Cancer Image Classification: A Genetic Programming Approach. Proceedings of the Genetic and Evolutionary Computation Conference. 1363–1372.
9.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2023). A New Genetic Programming Representation for Feature Learning in Skin Cancer Detection. 2 indexed citations
10.
Ain, Qurrat Ul, et al.. (2022). Loneliness and mental health related impacts of COVID-19: a narrative review. International Journal of Adolescent Medicine and Health. 35(1). 21–30. 9 indexed citations
11.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2022). Genetic programming for automatic skin cancer image classification. Expert Systems with Applications. 197. 116680–116680. 23 indexed citations
12.
Shahzad, Hasan, Qurrat Ul Ain, Amjad Ali Pasha, et al.. (2022). Double-diffusive natural convection energy transfer in magnetically influenced Casson fluid flow in trapezoidal enclosure with fillets. International Communications in Heat and Mass Transfer. 137. 106236–106236. 43 indexed citations
13.
Ain, Qurrat Ul, et al.. (2022). Haematological Changes in Hepatitis C (HCV) Patients. 16(4). 126–127. 2 indexed citations
14.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2022). Automatically Diagnosing Skin Cancers From Multimodality Images Using Two-Stage Genetic Programming. IEEE Transactions on Cybernetics. 53(5). 2727–2740. 14 indexed citations
15.
Ain, Qurrat Ul, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2020). A genetic programming approach to feature construction for ensemble learning in skin cancer detection. 1186–1194. 13 indexed citations
16.
Ain, Qurrat Ul, et al.. (2018). Convolutional neural network based image segmentation: a review. 26–26. 32 indexed citations
17.
Ain, Qurrat Ul, et al.. (2017). Levetiracetam Induced Increase in Creatine Phosphokinase Levels.. PubMed. 27(3). S63–S64. 8 indexed citations
18.
Subramanian, Vigneshwari, Qurrat Ul Ain, Lars‐Olof Pietilä, et al.. (2017). 3D proteochemometrics: using three-dimensional information of proteins and ligands to address aspects of the selectivity of serine proteases. MedChemComm. 8(5). 1037–1045. 6 indexed citations
19.
Ain, Qurrat Ul, et al.. (2015). Machine‐learning scoring functions to improve structure‐based binding affinity prediction and virtual screening. Wiley Interdisciplinary Reviews Computational Molecular Science. 5(6). 405–424. 254 indexed citations
20.
Ain, Qurrat Ul, Oscar Méndez‐Lucio, Isidro Cortés‐Ciriano, et al.. (2014). Modelling ligand selectivity of serine proteases using integrative proteochemometric approaches improves model performance and allows the multi-target dependent interpretation of features. Integrative Biology. 6(11). 1023–1033. 23 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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