H.A. Erlich

12.1k total citations · 2 hit papers
50 papers, 6.3k citations indexed

About

H.A. Erlich is a scholar working on Immunology, Genetics and Molecular Biology. According to data from OpenAlex, H.A. Erlich has authored 50 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Immunology, 18 papers in Genetics and 9 papers in Molecular Biology. Recurrent topics in H.A. Erlich's work include T-cell and B-cell Immunology (20 papers), Immune Cell Function and Interaction (17 papers) and Diabetes and associated disorders (11 papers). H.A. Erlich is often cited by papers focused on T-cell and B-cell Immunology (20 papers), Immune Cell Function and Interaction (17 papers) and Diabetes and associated disorders (11 papers). H.A. Erlich collaborates with scholars based in United States, United Kingdom and Switzerland. H.A. Erlich's co-authors include Russell Higuchi, Glenn T. Horn, Janelle A. Noble, Teodorica L. Bugawan, Christopher M. Long, David H. Gelfand, Randall K. Saiki, Norman Arnheim, S. Scharf and Kary B. Mullis and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

H.A. Erlich

49 papers receiving 6.0k citations

Hit Papers

Primer-directed enzymatic amplification of DNA with a the... 1988 2026 2000 2013 1988 1992 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H.A. Erlich United States 26 2.3k 1.8k 1.4k 812 565 50 6.3k
Hiroyuki Iwahana Japan 25 2.1k 0.9× 1.0k 0.6× 1.2k 0.8× 568 0.7× 231 0.4× 71 5.3k
Jeffrey J. Gorman Australia 40 3.5k 1.5× 1.2k 0.7× 924 0.7× 657 0.8× 382 0.7× 106 7.3k
Masato Orita Japan 7 3.1k 1.3× 1.3k 0.8× 447 0.3× 410 0.5× 339 0.6× 8 6.3k
Joanne N. Engel United States 51 5.5k 2.4× 1.7k 1.0× 1.4k 1.0× 1.4k 1.7× 584 1.0× 108 9.7k
Youichi Suzuki Japan 25 2.4k 1.0× 828 0.5× 1.2k 0.8× 696 0.9× 157 0.3× 78 5.9k
Göran Larson Sweden 49 4.3k 1.8× 1.2k 0.7× 1.3k 0.9× 758 0.9× 291 0.5× 184 8.6k
G. Galfré United Kingdom 30 3.8k 1.7× 547 0.3× 3.0k 2.1× 448 0.6× 423 0.7× 48 8.4k
Qunyuan Zhang United States 22 5.7k 2.4× 2.0k 1.2× 899 0.6× 667 0.8× 262 0.5× 41 10.4k
Olfert Landt Germany 43 3.1k 1.3× 857 0.5× 709 0.5× 983 1.2× 382 0.7× 141 8.1k
Karin Moelling Germany 49 6.3k 2.7× 1.1k 0.6× 1.6k 1.2× 1.1k 1.3× 524 0.9× 220 9.9k

Countries citing papers authored by H.A. Erlich

Since Specialization
Citations

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

Fields of papers citing papers by H.A. Erlich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H.A. Erlich. 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 H.A. Erlich. The network helps show where H.A. Erlich may publish in the future.

Co-authorship network of co-authors of H.A. Erlich

This figure shows the co-authorship network connecting the top 25 collaborators of H.A. Erlich. A scholar is included among the top collaborators of H.A. Erlich 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 H.A. Erlich. H.A. Erlich 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.
Erlich, H.A., Kurt Lohman, Steven J. Mack, et al.. (2009). Association analysis of SNPs in the IL4R locus with type I diabetes. Genes and Immunity. 10(S1). S33–S41. 12 indexed citations
2.
Rich, Stephen S., Beena Akolkar, Patrick Concannon, et al.. (2009). Current status and the future for the genetics of type I diabetes. Genes and Immunity. 10(S1). S128–S131. 4 indexed citations
3.
Ivansson, Emma, et al.. (2008). MHC loci affecting cervical cancer risk: distinguishing the effects of HLA-DQB1 and non-HLA genes TNF, LTA, TAP1 and TAP2. Genes and Immunity. 9(7). 613–623. 33 indexed citations
4.
Bodmer, J. G., Steven G. E. Marsh, E. D. Albert, et al.. (1999). Nomenclature for factors of the HLA system, 1998. European Journal of Immunogenetics. 26(2-3). 81–116. 6 indexed citations
5.
Trachtenberg, Elizabeth, et al.. (1996). Results of Expedition Humana. Tissue Antigens. 48(3). 174–181. 44 indexed citations
6.
Apple, R., et al.. (1994). Population screening with a PCR/immobilized SSO probe HLA- A test reveals new HLA-A alleles. Human Immunology. 40. 67–67. 1 indexed citations
7.
Titus, Emily, William Klitz, Olga Rickards, Gina M. DeStefano, & H.A. Erlich. (1993). Hla class-II evolution in nthe Cayapa indians of Ecuador. Human Immunology. 37. 16–16. 1 indexed citations
8.
Blake, Emily, et al.. (1992). Polymerase chain reaction (PCR) amplification and human leukocyte antigen (HLA)-DQ alpha oligonucleotide typing on biological evidence samples: casework experience.. PubMed. 37(3). 700–26. 63 indexed citations
9.
Bodmer, J. G., E. D. Albert, Walter F. Bodmer, et al.. (1992). Nomenclature for factors of theHLA system, 1991. Immunogenetics. 36(3). 135–148. 46 indexed citations
10.
Termijtelen, A., H.A. Erlich, Laura Braun, et al.. (1991). Oligonucleotide typing is a perfect tool to identify antigens stimulatory in the mixed lymphocyte culture. Human Immunology. 31(4). 241–245. 28 indexed citations
11.
Erlich, H.A., et al.. (1990). Letters to the Editor. Journal of Forensic Sciences. 35(5). 1017–1021. 2 indexed citations
12.
Bodmer, J. G., S. G. E. Marsh, Peter Parham, et al.. (1990). Nomenclature for factors of the HLA system, 1989. Tissue Antigens. 35(1). 1–8. 116 indexed citations
13.
Ristaldi, Maria Serafina, Mario Pirastu, Maria Cristina Rosatelli, et al.. (1989). Prenatal diagnosis of β‐thalassaemia in Mediterranean populations by dot blot analysis with DNA amplification and allele specific oligonucleotide probes. Prenatal Diagnosis. 9(9). 629–638. 52 indexed citations
14.
Erlich, H.A., et al.. (1989). Rapid prenatal diagnosis of beta thalassemia using DNA amplification and nonradioactive probes. Blood. 73(2). 372–374. 25 indexed citations
15.
Bugawan, Teodorica L., John A. Hansen, E.M. Mickelson, et al.. (1989). Analysis of HLA-DP Allelic Sequence Polymorphism Using the In Vitro Enzymatic Amplification of DPα and DPβ Loci. PubMed. 141(11). 321–322. 191 indexed citations
16.
Bowcock, A., Anuradha Ray, H.A. Erlich, & Pravinkumar B. Sehgal. (1989). The Molecular Genetics of Beta‐2 Interferon/Interleukin‐6 (IFNβ2/IL6)a. Annals of the New York Academy of Sciences. 557(1). 345–352. 5 indexed citations
17.
Erlich, H.A., et al.. (1989). Rapid prenatal diagnosis of beta thalassemia using DNA amplification and nonradioactive probes. Blood. 73(2). 372–374. 34 indexed citations
18.
Zwollo, Patty, et al.. (1988). 555 Sequence differences in HLA-DRβ genes between Amb a V responders and non-responders. Journal of Allergy and Clinical Immunology. 81(1). 307–307. 1 indexed citations
19.
Griffiths, Robert, Edward T. Blake, George F. Sensabaugh, et al.. (1988). Identification of individuality using non-radioactive oligonucleotide probes to analyze enzymatically amplified polymorphic DNA sequences. Human Immunology. 23(2). 107–107. 1 indexed citations
20.
Symington, Frank W., et al.. (1985). Differential Ia antigen expression by autologous human erythroid and B lymphoblastoid cell lines.. The Journal of Immunology. 135(2). 1026–1032. 22 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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