Michael Neat

1.7k citations
38 papers · 1.1k · h-index 18

Impact in

Papers in

Michael Neat

37 papers receiving 1.1k citations

Peers

Michael Neat
Comparison fields: 5 of 59
  • Hematology 516
  • Pathology and Forensic Medicine 262
  • Genetics 146
  • Oncology 192
  • Molecular Biology 460
Replace Emma Das‐Gupta with:
Emma Das‐Gupta United Kingdom
Barbara Gamberi Italy
Khalid Tobal United Kingdom
JM Cayuela France
Gianluigi Castoldi Italy
Fernando Ramos Spain
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K.F. Wong China
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Citations per field
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Citations per year

Countries citing papers authored by Michael Neat

Since Specialization
Citations

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

Fields of papers citing papers by Michael Neat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Neat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Neat Line = papers co-authored together Michael Neat links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000224
2 2000151
3 200389
4 200061
5 201644
6 200842
7 200141
8 199941
9 201339
10 200336
11 200135
12
Characterization of acute promyelocytic leukemia cases lacking the classic t(15;17): results of the European Working Party. Groupe Francais de Cytogenetique Hematologique, Groupe de Francais d'Hematologie Cellulaire, UK Cancer Cytogenetics Group and BIOMED 1 European Community-Concerted Action "Molecular Cytogenetic Diagnosis in Haematological Malignancies"
200030
13 201129
14 200528
15 201423
16 201723
17 200119
18 201019
19 200015
20 200014

About Michael Neat

Michael Neat is a scholar working on Hematology, Pathology and Forensic Medicine, Oncology, Molecular Biology and Genetics, having authored 38 papers that have together received 1.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (13 papers), Chronic Lymphocytic Leukemia Research (9 papers), Lymphoma Diagnosis and Treatment (7 papers), Genomic variations and chromosomal abnormalities (6 papers), Acute Lymphoblastic Leukemia research (6 papers), Viral-associated cancers and disorders (5 papers), Lung Cancer Treatments and Mutations (5 papers) and Chronic Myeloid Leukemia Treatments (3 papers). The work is most often cited by research in Hematology (516 citations), Pathology and Forensic Medicine (262 citations), Genetics (146 citations), Oncology (192 citations) and Molecular Biology (460 citations). Michael Neat has collaborated with scholars based in United Kingdom, Ireland and United States. Frequent co-authors include Tim Lister, A. Z. S. Rohatiner, John Amess, Nicola Foot, Debra M. Lillington, Ivana N. Micallef, Natalie J. Foot, Janet Matthews, Jude Fitzgibbon and T. Andrew Lister. Their work appears in journals such as British Journal of Haematology, Journal of Clinical Oncology, Cytogenetic and Genome Research, Blood and Genes Chromosomes and Cancer.

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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