Junaid Gamieldien

2.2k total citations
36 papers, 867 citations indexed

About

Junaid Gamieldien is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Junaid Gamieldien has authored 36 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 9 papers in Genetics and 8 papers in Infectious Diseases. Recurrent topics in Junaid Gamieldien's work include Tuberculosis Research and Epidemiology (5 papers), Bioinformatics and Genomic Networks (5 papers) and Genomics and Rare Diseases (4 papers). Junaid Gamieldien is often cited by papers focused on Tuberculosis Research and Epidemiology (5 papers), Bioinformatics and Genomic Networks (5 papers) and Genomics and Rare Diseases (4 papers). Junaid Gamieldien collaborates with scholars based in South Africa, United States and Switzerland. Junaid Gamieldien's co-authors include Burtram C. Fielding, Michael J. Berry, Nicolaas C. Gey van Pittius, Albert D. Beyers, Roland J. Siezen, Gordon D. Brown, Andrey Ptitsyn, Colleen Saunders, William R. Bishai and Alan Christoffels and has published in prestigious journals such as PLoS ONE, Scientific Reports and Genome biology.

In The Last Decade

Junaid Gamieldien

34 papers receiving 854 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junaid Gamieldien South Africa 15 408 306 302 138 88 36 867
Pramod Kumar Tiwari India 18 198 0.5× 359 1.2× 148 0.5× 101 0.7× 70 0.8× 59 832
Frédéric Boudou France 14 290 0.7× 324 1.1× 272 0.9× 258 1.9× 183 2.1× 18 921
Jacqueline Gonzales United States 7 769 1.9× 353 1.2× 568 1.9× 75 0.5× 377 4.3× 13 1.2k
Luke B. Snell United Kingdom 12 414 1.0× 190 0.6× 245 0.8× 117 0.8× 251 2.9× 40 921
Dorothy Fallows United States 22 908 2.2× 373 1.2× 743 2.5× 52 0.4× 217 2.5× 36 1.3k
Janisha Patel United Kingdom 13 249 0.6× 228 0.7× 440 1.5× 70 0.5× 139 1.6× 19 837
Qing Sun China 17 362 0.9× 276 0.9× 292 1.0× 21 0.2× 67 0.8× 55 790
Marc J. Eleveld Netherlands 21 100 0.2× 456 1.5× 214 0.7× 240 1.7× 57 0.6× 42 919
Ruijuan Zheng China 18 403 1.0× 310 1.0× 322 1.1× 28 0.2× 192 2.2× 50 831
Caitlin E. Edwards United States 11 859 2.1× 226 0.7× 162 0.5× 75 0.5× 172 2.0× 17 1.3k

Countries citing papers authored by Junaid Gamieldien

Since Specialization
Citations

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

Fields of papers citing papers by Junaid Gamieldien

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junaid Gamieldien

This figure shows the co-authorship network connecting the top 25 collaborators of Junaid Gamieldien. A scholar is included among the top collaborators of Junaid Gamieldien 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 Junaid Gamieldien. Junaid Gamieldien 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.
Saunders, Colleen, et al.. (2020). Exploring new genetic variants within COL5A1 intron 4‐exon 5 region and TGF‐β family with risk of anterior cruciate ligament ruptures. Journal of Orthopaedic Research®. 38(8). 1856–1865. 4 indexed citations
2.
Babenko, Vladimir N., et al.. (2019). FTO haplotyping underlines high obesity risk for European populations. BMC Medical Genomics. 12(S2). 46–46. 14 indexed citations
3.
Saunders, Colleen, et al.. (2018). Defining the molecular signatures of Achilles tendinopathy and anterior cruciate ligament ruptures: A whole-exome sequencing approach. PLoS ONE. 13(10). e0205860–e0205860. 19 indexed citations
4.
Heckmann, Jeannine M., et al.. (2018). Exome sequencing identifies novel dysferlin mutation in a family with pauci-symptomatic heterozygous carriers. BMC Medical Genetics. 19(1). 95–95. 3 indexed citations
5.
Malan‐Müller, Stefanie, Willie M. U. Daniels, Martin Kidd, et al.. (2017). The role of microRNAs in the therapeutic action of D-cycloserine in a post-traumatic stress disorder animal model. Psychiatric Genetics. 27(4). 139–151. 6 indexed citations
6.
Matsha, Tandi E., Carmen Pheiffer, Steve E. Humphries, et al.. (2016). Genome-Wide DNA Methylation in Mixed Ancestry Individuals with Diabetes and Prediabetes from South Africa. International Journal of Endocrinology. 2016. 1–11. 16 indexed citations
7.
Pillay, Balakrishna, et al.. (2016). Mycobacterium tuberculosis strains exhibit differential and strain-specific molecular signatures in pulmonary epithelial cells. Developmental & Comparative Immunology. 65. 321–329. 9 indexed citations
8.
Saunders, Colleen, et al.. (2016). Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes. Scientific Reports. 6(1). 19820–19820. 17 indexed citations
9.
Entfellner, Jean-Baka Domelevo, et al.. (2016). NetCapDB: measuring bioinformatics capacity development in Africa. BMC Research Notes. 9(1). 144–144. 3 indexed citations
10.
Mulder, Nicola, Alan Christoffels, Túlio de Oliveira, et al.. (2016). The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt. PLoS Computational Biology. 12(2). e1004395–e1004395. 14 indexed citations
11.
Glanzmann, Brigitte, et al.. (2016). A new tool for prioritization of sequence variants from whole exome sequencing data. PubMed. 11(1). 10–10. 7 indexed citations
12.
13.
Gamieldien, Junaid, et al.. (2015). Self-similarity of human protein interaction networks: a novel strategy of distinguishing proteins. Scientific Reports. 5(1). 7628–7628. 5 indexed citations
14.
Malan‐Müller, Stefanie, Willie M. U. Daniels, Edward J. Oakeley, et al.. (2015). Molecular mechanisms of D-cycloserine in facilitating fear extinction: insights from RNAseq. Metabolic Brain Disease. 31(1). 135–156. 5 indexed citations
15.
Gamieldien, Junaid, et al.. (2014). Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery. BMC Systems Biology. 8(1). 68–68. 10 indexed citations
16.
Choudhury, Ananyo, Scott Hazelhurst, Ayton Meintjes, et al.. (2014). Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance. BMC Genomics. 15(1). 437–437. 34 indexed citations
17.
18.
Gamieldien, Junaid, et al.. (2002). Eukaryotic genes in Mycobacterium tuberculosis could have a role in pathogenesis and immunomodulation. Trends in Genetics. 18(1). 5–8. 48 indexed citations
19.
Gamieldien, Junaid, et al.. (2002). Positive Selection Scanning Reveals Decoupling of Enzymatic Activities of Carbamoyl Phosphate Synthetase in Helicobacter pylori. Journal of Molecular Evolution. 54(4). 458–464. 7 indexed citations
20.
Gamieldien, Junaid & Yoshihide Hayashizaki. (1998). A Genome-Level Search for Bacterial Genes on Which Positive Selection May Operate. Proceedings Genome Informatics Workshop/Genome informatics. 9. 269–270. 1 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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