Yaser Daanial Khan

3.6k total citations
102 papers, 2.7k citations indexed

About

Yaser Daanial Khan is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Yaser Daanial Khan has authored 102 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Molecular Biology, 13 papers in Computer Vision and Pattern Recognition and 12 papers in Computational Theory and Mathematics. Recurrent topics in Yaser Daanial Khan's work include Machine Learning in Bioinformatics (70 papers), RNA and protein synthesis mechanisms (41 papers) and Genomics and Phylogenetic Studies (40 papers). Yaser Daanial Khan is often cited by papers focused on Machine Learning in Bioinformatics (70 papers), RNA and protein synthesis mechanisms (41 papers) and Genomics and Phylogenetic Studies (40 papers). Yaser Daanial Khan collaborates with scholars based in Pakistan, Saudi Arabia and United States. Yaser Daanial Khan's co-authors include Nouman Rasool, Sher Afzal Khan, Waqar Hussain, Kuo‐Chen Chou, Ahmad Hassan Butt, Sharaf J. Malebary, Sheraz Naseer, Farooq Ahmad, Asghar Ali Shah and Muhammad Khalid Mahmood and has published in prestigious journals such as PLoS ONE, Analytical Biochemistry and Scientific Reports.

In The Last Decade

Yaser Daanial Khan

95 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yaser Daanial Khan Pakistan 37 2.3k 276 145 142 107 102 2.7k
Abdollah Dehzangi United States 32 2.6k 1.1× 472 1.7× 367 2.5× 177 1.2× 104 1.0× 102 3.5k
Maqsood Hayat Pakistan 36 3.0k 1.3× 471 1.7× 258 1.8× 77 0.5× 289 2.7× 72 3.5k
Shahid Akbar Pakistan 26 1.2k 0.5× 278 1.0× 237 1.6× 89 0.6× 250 2.3× 40 1.8k
Xiaolei Zhu China 23 1.1k 0.5× 283 1.0× 188 1.3× 36 0.3× 40 0.4× 64 1.6k
Bo Liao China 29 1.6k 0.7× 216 0.8× 253 1.7× 79 0.6× 32 0.3× 111 2.1k
Yu‐Yen Ou Taiwan 24 1.2k 0.5× 144 0.5× 332 2.3× 83 0.6× 62 0.6× 73 1.8k
Xiucai Ye Japan 18 801 0.4× 219 0.8× 184 1.3× 85 0.6× 124 1.2× 101 1.2k
Muhammad Tahir Pakistan 21 1.0k 0.5× 101 0.4× 202 1.4× 47 0.3× 93 0.9× 46 1.5k
Yijie Ding China 37 3.4k 1.5× 1.2k 4.2× 337 2.3× 89 0.6× 121 1.1× 181 4.3k
Farman Ali Pakistan 30 1.7k 0.8× 441 1.6× 468 3.2× 582 4.1× 252 2.4× 90 3.0k

Countries citing papers authored by Yaser Daanial Khan

Since Specialization
Citations

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

Fields of papers citing papers by Yaser Daanial Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yaser Daanial Khan. 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 Yaser Daanial Khan. The network helps show where Yaser Daanial Khan may publish in the future.

Co-authorship network of co-authors of Yaser Daanial Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Yaser Daanial Khan. A scholar is included among the top collaborators of Yaser Daanial Khan 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 Yaser Daanial Khan. Yaser Daanial Khan 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.
Khan, Yaser Daanial, Tamim Alkhalifah, Fahad Alturise, & Ahmad Hassan Butt. (2024). DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest. Methods. 231. 26–36. 2 indexed citations
2.
Alturise, Fahad, et al.. (2024). Gluconeogenesis unraveled: A proteomic Odyssey with machine learning. Methods. 232. 29–42.
3.
Alkhalifah, Tamim, et al.. (2024). GCF-MLD: Integrated Approach for Money Laundering Detection Using Machine Learning and Graph Network Analysis. IEEE Access. 12. 183961–183972. 1 indexed citations
4.
Butt, Ahmad Hassan, Tamim Alkhalifah, Fahad Alturise, & Yaser Daanial Khan. (2023). Ensemble Learning for Hormone Binding Protein Prediction: A Promising Approach for Early Diagnosis of Thyroid Hormone Disorders in Serum. Diagnostics. 13(11). 1940–1940. 7 indexed citations
5.
Alturise, Fahad, et al.. (2023). Hemolytic-Pred: A machine learning-based predictor for hemolytic proteins using position and composition-based features. Digital Health. 9. 589824451–589824451. 8 indexed citations
6.
Alotaibi, Fahad & Yaser Daanial Khan. (2023). A Framework for Prediction of Oncogenomic Progression Aiding Personalized Treatment of Gastric Cancer. Diagnostics. 13(13). 2291–2291. 1 indexed citations
7.
Alghamdi, Wajdi, Muhammad Attique, Ebraheem Alzahrani, Malik Zaka Ullah, & Yaser Daanial Khan. (2022). LBCEPred: a machine learning model to predict linear B-cell epitopes. Briefings in Bioinformatics. 23(3). 23 indexed citations
8.
Shah, Asghar Ali, Fahad Alturise, Tamim Alkhalifah, & Yaser Daanial Khan. (2022). Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations. International Journal of Molecular Sciences. 23(19). 11539–11539. 13 indexed citations
9.
Malebary, Sharaf J., et al.. (2021). ProtoPred: Advancing Oncological Research Through Identification of Proto-Oncogene Proteins. IEEE Access. 9. 68788–68797. 37 indexed citations
10.
Khan, Yaser Daanial, Nabeel Sabir Khan, Sheraz Naseer, & Ahmad Hassan Butt. (2021). iSUMOK-PseAAC: prediction of lysine sumoylation sites using statistical moments and Chou’s PseAAC. PeerJ. 9. e11581–e11581. 39 indexed citations
11.
Khan, Yaser Daanial, et al.. (2021). iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers. Applied Bionics and Biomechanics. 2021. 1–15. 9 indexed citations
12.
Hussain, Waqar, et al.. (2021). iTSP-PseAAC: Identifying Tumor Suppressor Proteins by Using Fully Connected Neural Network and PseAAC. Current Bioinformatics. 16(5). 700–709. 28 indexed citations
13.
Malebary, Sharaf J., Ebraheem Alzahrani, & Yaser Daanial Khan. (2021). A comprehensive tool for accurate identification of methyl-Glutamine sites. Journal of Molecular Graphics and Modelling. 110. 108074–108074. 11 indexed citations
14.
Alghamdi, Wajdi, Ebraheem Alzahrani, Malik Zaka Ullah, & Yaser Daanial Khan. (2021). 4mC-RF: Improving the prediction of 4mC sites using composition and position relative features and statistical moment. Analytical Biochemistry. 633. 114385–114385. 20 indexed citations
15.
Naseer, Sheraz, et al.. (2020). Optimization of serine phosphorylation prediction in proteins by comparing human engineered features and deep representations. Analytical Biochemistry. 615. 114069–114069. 51 indexed citations
16.
Naseer, Sheraz, Waqar Hussain, Yaser Daanial Khan, & Nouman Rasool. (2020). iPhosS(Deep)-PseAAC: Identification of Phosphoserine Sites in Proteins Using Deep Learning on General Pseudo Amino Acid Compositions. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3). 1703–1714. 46 indexed citations
17.
Khan, Yaser Daanial, Ebraheem Alzahrani, Wajdi Alghamdi, & Malik Zaka Ullah. (2020). Sequence-based Identification of Allergen Proteins Developed by Integration of PseAAC and Statistical Moments via 5-Step Rule. Current Bioinformatics. 15(9). 1046–1055. 40 indexed citations
18.
Malebary, Sharaf J., et al.. (2019). iCrotoK-PseAAC: Identify lysine crotonylation sites by blending position relative statistical features according to the Chou’s 5-step rule. PLoS ONE. 14(11). e0223993–e0223993. 54 indexed citations
19.
Khan, Yaser Daanial, et al.. (2018). pSSbond-PseAAC: Prediction of disulfide bonding sites by integration of PseAAC and statistical moments. Journal of Theoretical Biology. 463. 47–55. 65 indexed citations
20.
Rasool, Nouman, et al.. (2017). Prediction of N-linked glycosylation sites using position relative features and statistical moments. PLoS ONE. 12(8). e0181966–e0181966. 81 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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