Dan Ofer

2.1k citations
17 papers · 881 indexed · 2 hit papers · h-index 10
Topics
Machine Learning in Bioinformatics (7 papers)RNA and protein synthesis mechanisms (4 papers)Genomics and Phylogenetic Studies (3 papers)

In The Last Decade

Dan Ofer

15 papers receiving 865 citations

Hit Papers

ProteinBERT: a universal deep-learning model of protein s...202120262022202420222021100200300400

Peers

Dan Ofer
Comparison fields: 5 of 97
  • Molecular Biology 697
  • Computational Theory and Mathematics 110
  • Artificial Intelligence 95
  • Microbiology 48
  • Radiology, Nuclear Medicine and Imaging 47
Replace Nadav Brandes with:
Nadav Brandes Israel
Grigory Khimulya Russia
Xosé M. Fernández United Kingdom
Marcin J. Skwark Sweden
Noelia Ferruz Spain
Chunhua Li China
Joshua Meier United States
Ghalia Rehawi Germany
Kelly P. Brock United States
Ethan C. Alley United States
Dan Ofer relative to Nadav Brandes Israel Nadav Brandes's profile →
Citations per field
00.5×10×14×
Nadav Brandes · 1×
Citations per year

Countries citing papers authored by Dan Ofer

Since Specialization
Citations

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

Fields of papers citing papers by Dan Ofer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Ofer

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Ofer. A scholar is included among the top collaborators of Dan Ofer 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 Dan Ofer. Dan Ofer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 0
2 1
3 4
4 11
5
ProteinBERT: a universal deep-learning model of protein sequence and functionbreakdown →
451
6 5
7 7
8 19
9
The language of proteins: NLP, machine learning & protein sequencesbreakdown →
217
10 20
11 9
12 16
13 63
14 0
15 12
16 34
17 12

About Dan Ofer

Dan Ofer is a scholar working on Statistics, Probability and Uncertainty, Visual Arts and Performing Arts and Molecular Biology, having authored 17 papers that have together received 881 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (7 papers), RNA and protein synthesis mechanisms (4 papers) and Genomics and Phylogenetic Studies (3 papers). The work is most often cited by research in Molecular Biology (697 citations), Health Informatics (11 citations) and Microbiology (48 citations). Dan Ofer has collaborated with scholars based in Israel, Canada and United States. Frequent co-authors include Michal Linial, Nadav Brandes, Nadav Rappoport, Lior Rokach, Noa Dagan, Adi Shraibman, Dafna Shahaf, Tali Sahar, Niv Cohen and Yedid Hoshen. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and IEEE Access.

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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