Tanita Wein

2.4k citations
25 papers · 1.3k indexed · 3 hit papers · h-index 18

Tanita Wein

24 papers receiving 1.3k citations

Hit Papers

Clustering predicted structures at the scale of the known...160202220262023202450100150

Peers

Tanita Wein
Comparison fields: 5 of 113
  • Molecular Medicine 184
  • Endocrinology 122
  • Ecology 422
  • Molecular Biology 683
  • Immunology 161
Replace Vianney Pichereau with:
Vianney Pichereau France
Scott Clingenpeel United States
Hoda Khouri United States
Takatomo Fujisawa Japan
Yan Wei Lim United States
Isabel M. López‐Lara Mexico
Sabine Gronow Germany
Tiffany C. Williams United States
Gipsi Lima‐Mendez Belgium
Tanita Wein relative to Vianney Pichereau France Vianney Pichereau's profile →
Citations per field
00.5×4.7×
Vianney Pichereau · 1×
Citations per year

Countries citing papers authored by Tanita Wein

Since Specialization
Citations

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

Fields of papers citing papers by Tanita Wein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20253
3 202510
4
Clustering predicted structures at the scale of the known protein universebreakdown →
2023160
5 20233
6 202223
7 202296
8
Bacterial gasdermins reveal an ancient mechanism of cell deathbreakdown →
2022165
9 202142
10 202119
11 202038
12 202035
13 201920
14 201962
15 201930
16 2019157
17 20193
18 201867
19 201833
20 201768

About Tanita Wein

Tanita Wein is a scholar working on Molecular Medicine, Parasitology and Ecology, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (8 papers), Microbial Community Ecology and Physiology (6 papers), Evolution and Genetic Dynamics (6 papers), Genomics and Phylogenetic Studies (5 papers), Bacteriophages and microbial interactions (3 papers), Protist diversity and phylogeny (3 papers), Plant Pathogenic Bacteria Studies (3 papers) and Bacterial Genetics and Biotechnology (3 papers). The work is most often cited by research in Molecular Medicine (184 citations), Endocrinology (122 citations) and Ecology (422 citations). Tanita Wein has collaborated with scholars based in Germany, Israel and United States. Frequent co-authors include Tal Dagan, Rotem Sorek, Nils F. Hülter, Itzhak Mizrahi, Erez Yirmiya, Philip J. Kranzusch, Katrin Hammerschmidt, Christian Woehle, Gil Amitai and Yaara Oppenheimer‐Shaanan. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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