S Hæggman

16 papers receiving 1.1k citations

S Hæggman's Hit Papers

Guidelines for the validation and application of typing methods for use in bacterial epidemiology 2007 · 649 citations
6490+6+12Years since publication200400600

Peers

S Hæggman
Comparison fields: 5 of 86
  • Molecular Medicine 328
  • Endocrinology 243
  • Clinical Biochemistry 260
  • Infectious Diseases 425
  • Applied Microbiology and Biotechnology 40
Replace Robert D. Arbeit with:
Robert D. Arbeit United States
J. Breuil France
Joshua B. Daniels United States
Hazel M. Aucken United Kingdom
Maria Finn Sweden
Natacha Couto Netherlands
A. Dublanchet France
Ivonne Stamm Germany
Sampa Mukherjee United States
Christiane Werckenthin Germany
S Hæggman relative to Robert D. Arbeit United States Robert D. Arbeit's profile →
Citations per field
00.5×8.5×
Robert D. Arbeit · 1×
Citations per year

Countries citing papers authored by S Hæggman

Since Specialization
Citations

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

Fields of papers citing papers by S Hæggman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside S Hæggman, 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 S Hæggman Line = papers co-authored together S Hæggman links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Guidelines for the validation and application of typing methods for use in bacterial epidemiology
Hit paper breakdown →
2007649
2 2004129
3 199576
4 200252
5 198238
6 199735
7 200928
8 199728
9
The humoral antibody response to Shigella dysenteriae type 1 infection, as determined by ELISA.
198428
10 200327
11 200626
12 200425
13 200719
14 199818
15 199215
16 20096

About S Hæggman

S Hæggman is a scholar working on Infectious Diseases, Molecular Medicine, Molecular Biology, Epidemiology and Endocrinology, having authored 16 papers that have together received 1.2k indexed citations. Recurring topics across this work include Antimicrobial Resistance in Staphylococcus (7 papers), Antibiotic Resistance in Bacteria (6 papers), Bacterial Identification and Susceptibility Testing (4 papers), Genomics and Phylogenetic Studies (3 papers), Pneumonia and Respiratory Infections (2 papers), Bacterial biofilms and quorum sensing (2 papers), Escherichia coli research studies (2 papers) and Enterobacteriaceae and Cronobacter Research (2 papers). The work is most often cited by research in Molecular Medicine (328 citations), Endocrinology (243 citations), Clinical Biochemistry (260 citations), Infectious Diseases (425 citations) and Applied Microbiology and Biotechnology (40 citations). S Hæggman has collaborated with scholars based in Sweden, United States and Netherlands. Frequent co-authors include Sylvain Brisse, Lenie Dijkshoorn, Vivian Fussing, Peter Gerner‐Smidt, Edward J. Feil, Panayotis T. Tassios, Alex van Belkum, B Cookson, Norman K. Fry and Marc Struelens. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, Clinical Microbiology and Infection, Eurosurveillance, Acta Paediatrica and Journal of Clinical Microbiology.

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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