Rolf Apweiler

61.6k citations
167 papers · 25.7k · 11 hit papers · h-index 48

Impact in

    • Genomics and Phylogenetic Studies
    • Bioinformatics and Genomic Networks
    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Glycosylation and Glycoproteins Research
    • Protein Structure and Dynamics
    • Biomedical Text Mining and Ontologies
  • Spectroscopy top 0.1%
    • Advanced Proteomics Techniques and Applications

Papers in

    • Genomics and Phylogenetic Studies 64
    • Bioinformatics and Genomic Networks 51
    • Machine Learning in Bioinformatics 46
    • Biomedical Text Mining and Ontologies 33
    • RNA and protein synthesis mechanisms 24
    • Gene expression and cancer classification 16
    • Genetics, Bioinformatics, and Biomedical Research 15
    • Advanced Proteomics Techniques and Applications 68

Rolf Apweiler

165 papers receiving 25.0k citations

Rolf Apweiler's Hit Papers

Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads 2009 · 1.3k citations
1.3k0+9+19Years since publication10002.0k3.0k4.0k5.0k

Peers

Rolf Apweiler
Comparison fields: 5 of 194
  • Molecular Biology 19.0k
  • Spectroscopy 2.8k
  • Plant Science 3.8k
  • Genetics 2.8k
  • Aging 170
Replace Masaru Tomita with:
Masaru Tomita Japan
Amos Bairoch Switzerland
Adam Godzik United States
Edward M. Marcotte United States
Burkhard Rost United States
Stephen H. Bryant United States
Howard R. Morris United Kingdom
Benno Schwikowski France
Steven E. Brenner United States
Geoffrey J. Barton United Kingdom
Rolf Apweiler relative to Masaru Tomita Japan Masaru Tomita's profile →
Citations per field
00.5×1.7×
Masaru Tomita · 1×
Citations per year

Countries citing papers authored by Rolf Apweiler

Since Specialization
Citations

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

Fields of papers citing papers by Rolf Apweiler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 167 papers — load more, or switch the sort, to bring in the rest.

#Work
1
UniProt: the Universal Protein knowledgebase
Hit paper breakdown →
20035875
2
The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1999
Hit paper breakdown →
19992619
3
InterProScan: protein domains identifier
Hit paper breakdown →
20052244
4
InterProScan – an integration platform for the signature-recognition methods in InterPro
Hit paper breakdown →
20012214
5
On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database
Hit paper breakdown →
19991489
6
Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads
Hit paper breakdown →
20091269
7
Evaluation of methods for the prediction of membrane spanning regions
Hit paper breakdown →
2001946
8
The InterPro database, an integrated documentation resource for protein families, domains and functional sites
Hit paper breakdown →
2001825
9
QuickGO: a web-based tool for Gene Ontology searching
Hit paper breakdown →
2009672
10
The International Protein Index: An integrated database for proteomics experiments
Hit paper breakdown →
2004600
11
The SWISS-PROT protein sequence data bank and its supplement TrEMBL
Hit paper breakdown →
1997555
12 2008452
13 2005443
14 2007319
15 2003273
16 2009213
17 2008194
18 2003176
19 2003154
20 2006151

About Rolf Apweiler

Rolf Apweiler is a scholar working on Molecular Biology, Spectroscopy, Information Systems and Management, Artificial Intelligence and Genetics, having authored 167 papers that have together received 25.7k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (68 papers), Genomics and Phylogenetic Studies (64 papers), Bioinformatics and Genomic Networks (51 papers), Machine Learning in Bioinformatics (46 papers), Biomedical Text Mining and Ontologies (33 papers), RNA and protein synthesis mechanisms (24 papers), Gene expression and cancer classification (16 papers) and Genetics, Bioinformatics, and Biomedical Research (15 papers). The work is most often cited by research in Molecular Biology (19.0k citations), Spectroscopy (2.8k citations), Plant Science (3.8k citations), Genetics (2.8k citations) and Aging (170 citations). Rolf Apweiler has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Amos Bairoch, Evgeny M. Zdobnov, Nicola Mulder, Rodrigo López, Steffen Möller, Michael D. R. Croning, S. Pillai, Emmanuel Quévillon, Naomi Harte and Henning Hermjakob. Their work appears in journals such as PROTEOMICS, Bioinformatics, Nucleic Acids Research, Comparative and Functional Genomics and Molecular & Cellular Proteomics.

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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