Adeel Malik

2.3k total citations
49 papers, 1.0k citations indexed

About

Adeel Malik is a scholar working on Molecular Biology, Immunology and Pharmacology. According to data from OpenAlex, Adeel Malik has authored 49 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 7 papers in Immunology and 6 papers in Pharmacology. Recurrent topics in Adeel Malik's work include Machine Learning in Bioinformatics (10 papers), Genomics and Phylogenetic Studies (9 papers) and Glycosylation and Glycoproteins Research (7 papers). Adeel Malik is often cited by papers focused on Machine Learning in Bioinformatics (10 papers), Genomics and Phylogenetic Studies (9 papers) and Glycosylation and Glycoproteins Research (7 papers). Adeel Malik collaborates with scholars based in South Korea, India and Saudi Arabia. Adeel Malik's co-authors include Shandar Ahmad, Balachandran Manavalan, Sathiyamoorthy Subramaniyam, Seung Bum Kim, Gwang Lee, Deok‐Chun Yang, Chang-Bae Kim, Ahmad Firoz, Lizhen Cui and Ran Su and has published in prestigious journals such as PLoS ONE, The FASEB Journal and International Journal of Molecular Sciences.

In The Last Decade

Adeel Malik

47 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adeel Malik South Korea 17 723 97 83 82 60 49 1.0k
Dilmurat Yusuf Germany 12 525 0.7× 70 0.7× 73 0.9× 52 0.6× 65 1.1× 15 793
Luciano Pirone Italy 21 798 1.1× 52 0.5× 53 0.6× 88 1.1× 65 1.1× 70 1.2k
Joon Shin Singapore 21 753 1.0× 39 0.4× 33 0.4× 116 1.4× 37 0.6× 41 1.1k
Angelo Palmigiano Italy 20 623 0.9× 21 0.2× 77 0.9× 179 2.2× 99 1.6× 41 1.2k
Liang Huang China 19 591 0.8× 109 1.1× 18 0.2× 67 0.8× 87 1.4× 48 958
Jonathan G. Swoboda United States 14 804 1.1× 136 1.4× 29 0.3× 113 1.4× 72 1.2× 16 1.5k
David T. Chin United States 14 780 1.1× 40 0.4× 50 0.6× 198 2.4× 35 0.6× 16 1.3k
Flora Cozzolino Italy 20 675 0.9× 40 0.4× 14 0.2× 106 1.3× 81 1.4× 48 1.1k
Stephanie Kim United States 13 914 1.3× 22 0.2× 58 0.7× 61 0.7× 135 2.3× 29 1.4k

Countries citing papers authored by Adeel Malik

Since Specialization
Citations

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

Fields of papers citing papers by Adeel Malik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adeel Malik

This figure shows the co-authorship network connecting the top 25 collaborators of Adeel Malik. A scholar is included among the top collaborators of Adeel Malik 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 Adeel Malik. Adeel Malik 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.
2.
Malik, Adeel, Majid Rasool Kamli, Jamal S. M. Sabir, et al.. (2024). APLpred: A machine learning-based tool for accurate prediction and characterization of asparagine peptide lyases using sequence-derived optimal features. Methods. 229. 133–146. 5 indexed citations
3.
Ghosh, Arpita, Majid Rasool Kamli, Hyung Wook Kwon, et al.. (2024). The Chinese mitten crab (Eriocheir sinensis) and its microbiome: A review. Aquaculture. 595. 741518–741518. 8 indexed citations
4.
Malik, Adeel, et al.. (2024). Comparison of Bacterial Community Composition in Gut of Chinese Mitten Crabs from Three Distinct Rivers in Korea. Fishes. 9(4). 144–144. 3 indexed citations
5.
Malik, Adeel, et al.. (2024). Development of a two-layer machine learning model for the forensic application of legal and illegal poppy classification based on sequence data. Forensic Science International Genetics. 71. 103061–103061. 1 indexed citations
6.
Malik, Adeel, et al.. (2023). RDR100: A Robust Computational Method for Identification ofKrüppel-like Factors. Current Bioinformatics. 19(6). 584–599. 1 indexed citations
7.
8.
Pham, Nhat Truong, et al.. (2023). H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA. Briefings in Bioinformatics. 25(1). 37 indexed citations
9.
Firoz, Ahmad, et al.. (2023). PRR-HyPred: A two-layer hybrid framework to predict pattern recognition receptors and their families by employing sequence encoded optimal features. International Journal of Biological Macromolecules. 234. 123622–123622. 9 indexed citations
10.
Malik, Adeel, Sathiyamoorthy Subramaniyam, Chang-Bae Kim, & Balachandran Manavalan. (2021). SortPred: The first machine learning based predictor to identify bacterial sortases and their classes using sequence-derived information. Computational and Structural Biotechnology Journal. 20. 165–174. 24 indexed citations
11.
Wei, Leyi, Wenjia He, Adeel Malik, et al.. (2020). Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework. Briefings in Bioinformatics. 22(4). 118 indexed citations
12.
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Sheikh, Ishfaq A., et al.. (2017). In silico identification of genes involved in chronic metabolic acidosis. Life Sciences. 192. 246–252. 2 indexed citations
14.
Malik, Adeel, Eun Ju Lee, Arif Tasleem Jan, et al.. (2015). Network Analysis for the Identification of Differentially Expressed Hub Genes Using Myogenin Knock-down Muscle Satellite Cells. PLoS ONE. 10(7). e0133597–e0133597. 21 indexed citations
15.
Malik, Adeel, et al.. (2014). Community-Based Network Study of Protein-Carbohydrate Interactions in Plant Lectins Using Glycan Array Data. PLoS ONE. 9(4). e95480–e95480. 15 indexed citations
16.
Kamli, Majid Rasool, et al.. (2014). Expression of Transthyretin during bovine myogenic satellite cell differentiation. In Vitro Cellular & Developmental Biology - Animal. 50(8). 756–765. 7 indexed citations
17.
Lee, Eun Ju, Adeel Malik, Jihoe Kim, et al.. (2014). Identification of Genes Differentially Expressed in Myogenin Knock-Down Bovine Muscle Satellite Cells during Differentiation through RNA Sequencing Analysis. PLoS ONE. 9(3). e92447–e92447. 40 indexed citations
18.
Lee, Eun Ju, Majid Rasool Kamli, Adeel Malik, et al.. (2013). Expressed Sequence Tags for Bovine Muscle Satellite Cells, Myotube Formed-Cells and Adipocyte-Like Cells. PLoS ONE. 8(11). e79780–e79780. 14 indexed citations
19.
Malik, Adeel, Ahmad Firoz, Vivekanand Jha, E. Sunderasan, & Shandar Ahmad. (2010). Modeling the three-dimensional structures of an unbound single-chain variable fragment (scFv) and its hypothetical complex with a Corynespora cassiicola toxin, cassiicolin. Journal of Molecular Modeling. 16(12). 1883–1893. 4 indexed citations
20.
Malik, Adeel, Siti Arija M. Arif, Shandar Ahmad, & E. Sunderasan. (2007). A molecular and in silico characterization of Hev b 4, a glycosylated latex allergen. International Journal of Biological Macromolecules. 42(2). 185–190. 7 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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