Andrew M. Collins

3.1k total citations
69 papers, 2.0k citations indexed

About

Andrew M. Collins is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Andrew M. Collins has authored 69 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Immunology, 29 papers in Radiology, Nuclear Medicine and Imaging and 19 papers in Molecular Biology. Recurrent topics in Andrew M. Collins's work include T-cell and B-cell Immunology (30 papers), Monoclonal and Polyclonal Antibodies Research (29 papers) and Glycosylation and Glycoproteins Research (12 papers). Andrew M. Collins is often cited by papers focused on T-cell and B-cell Immunology (30 papers), Monoclonal and Polyclonal Antibodies Research (29 papers) and Glycosylation and Glycoproteins Research (12 papers). Andrew M. Collins collaborates with scholars based in Australia, United States and United Kingdom. Andrew M. Collins's co-authors include Katherine Jackson, Bruno Gaëta, William A. Sewell, Corey T. Watson, Scott D. Boyd, Frank Marken, Gur Yaari, Michael R. Edwards, William Lees and Yan Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Andrew M. Collins

68 papers receiving 1.9k citations

Peers

Andrew M. Collins
Hae Won Sohn United States
Stefan Miltenyi Germany
John A. Gebe United States
P Parham United States
Jin‐huan Liu United States
Haruo Kozono Japan
A Pierres France
Л. К. Эрнст United States
Martyn K. Robinson United Kingdom
Franco Calabi United Kingdom
Hae Won Sohn United States
Andrew M. Collins
Citations per year, relative to Andrew M. Collins Andrew M. Collins (= 1×) peers Hae Won Sohn

Countries citing papers authored by Andrew M. Collins

Since Specialization
Citations

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

Fields of papers citing papers by Andrew M. Collins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew M. Collins. 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 Andrew M. Collins. The network helps show where Andrew M. Collins may publish in the future.

Co-authorship network of co-authors of Andrew M. Collins

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew M. Collins. A scholar is included among the top collaborators of Andrew M. Collins 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 Andrew M. Collins. Andrew M. Collins 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.
Peres, Ayelet, William Lees, Oscar L. Rodriguez, et al.. (2023). IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data. Nucleic Acids Research. 51(16). e86–e86. 12 indexed citations
2.
Lees, William, Scott Christley, Ayelet Peres, et al.. (2023). AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets. SHILAP Revista de lepidopterología. 10. 100025–100025. 9 indexed citations
3.
Collins, Andrew M., Gur Yaari, Adrian J. Shepherd, William Lees, & Corey T. Watson. (2020). Germline immunoglobulin genes: Disease susceptibility genes hidden in plain sight?. Current Opinion in Systems Biology. 24. 100–108. 24 indexed citations
4.
Lees, William, Christian E. Busse, Martin Corcoran, et al.. (2019). OGRDB: a reference database of inferred immune receptor genes. Nucleic Acids Research. 48(D1). D964–D970. 39 indexed citations
5.
Gidoni, Moriah, Omri Snir, Ayelet Peres, et al.. (2019). Mosaic deletion patterns of the human antibody heavy chain gene locus shown by Bayesian haplotyping. Nature Communications. 10(1). 628–628. 67 indexed citations
6.
Watson, Corey T., Justin T. Kos, William S. Gibson, et al.. (2019). A comparison of immunoglobulin IGHV , IGHD and IGHJ genes in wild‐derived and classical inbred mouse strains. Immunology and Cell Biology. 97(10). 888–901. 25 indexed citations
7.
Collins, Andrew M. & Katherine Jackson. (2017). On being the right size: antibody repertoire formation in the mouse and human. Immunogenetics. 70(3). 143–158. 27 indexed citations
8.
Jackson, Katherine, et al.. (2015). DJ Pairing during VDJ Recombination Shows Positional Biases That Vary among Individuals with Differing IGHD Locus Immunogenotypes. The Journal of Immunology. 196(3). 1158–1164. 19 indexed citations
9.
Collins, Andrew M.. (2012). Callisthenes on Olympias and Alexander’s divine birth. Queensland's institutional digital repository (The University of Queensland). 26(10). 1–14. 2 indexed citations
10.
Marken, Frank, John D. Watkins, & Andrew M. Collins. (2011). Ion-transfer- and photo-electrochemistry at liquid|liquid|solid electrode triple phase boundary junctions: perspectives. Physical Chemistry Chemical Physics. 13(21). 10036–10036. 30 indexed citations
11.
Boyd, Scott D., Bruno Gaëta, Katherine Jackson, et al.. (2010). Individual Variation in the Germline Ig Gene Repertoire Inferred from Variable Region Gene Rearrangements. The Journal of Immunology. 184(12). 6986–6992. 184 indexed citations
12.
Chen, Zhiliang, Andrew M. Collins, Yan Wang, & Bruno Gaëta. (2010). Clustering-based identification of clonally-related immunoglobulin gene sequence sets. PubMed. 6(Suppl 1). S4–S4. 30 indexed citations
13.
Jackson, Katherine, Bruno Gaëta, & Andrew M. Collins. (2007). Identifying highly mutated IGHD genes in the junctions of rearranged human immunoglobulin heavy chain genes. Journal of Immunological Methods. 324(1-2). 26–37. 9 indexed citations
14.
Jackson, Katherine, et al.. (2006). Use of IGHJ and IGHD gene mutations in analysis of immunoglobulin sequences for the prognosis of chronic lymphocytic leukemia. Leukemia Research. 31(9). 1247–1252. 10 indexed citations
15.
Jackson, Nicole, Hongwei Wang, Nicodemus Tedla, et al.. (2005). IL-15 induces mast cell migration via a pertussis toxin-sensitive receptor. European Journal of Immunology. 35(8). 2376–2385. 18 indexed citations
16.
Collins, Andrew M., et al.. (2004). Partitioning of Rearranged Ig Genes by Mutation Analysis Demonstrates D-D Fusion and V Gene Replacement in the Expressed Human Repertoire. The Journal of Immunology. 172(1). 340–348. 22 indexed citations
17.
18.
Qi, Jian, Richard L Stevens, Robert Wadley, et al.. (2002). IL-16 Regulation of Human Mast Cells/Basophils and Their Susceptibility to HIV-1. The Journal of Immunology. 168(8). 4127–4134. 24 indexed citations
19.
Mitchell, Andrew J., et al.. (2002). The Biological Activity of Serum IgE Changes over the Course of a Primary Response. Scandinavian Journal of Immunology. 55(1). 33–43. 10 indexed citations
20.
Collins, Andrew M., et al.. (1995). Antigen Valency as a Determinant of the Responsiveness of IgE-Sensitised Rat Basophil Leukemia Cells. International Archives of Allergy and Immunology. 107(4). 547–556. 17 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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