Amarda Shehu

3.4k citations
149 papers · 2.3k indexed · 1 hit paper · h-index 25
Topics
Protein Structure and Dynamics (104 papers)Enzyme Structure and Function (41 papers)Machine Learning in Bioinformatics (35 papers)
Partner nations
United StatesIsraelSpain

In The Last Decade

Amarda Shehu

141 papers receiving 2.2k citations

Hit Papers

Deep learning improves antimicrobial peptide recognition20182026202020232018100200300

Peers

Amarda Shehu
Comparison fields: 5 of 155
  • Molecular Biology 1.9k
  • Materials Chemistry 543
  • Microbiology 342
  • Computational Theory and Mathematics 297
  • Spectroscopy 162
Replace Gianluca Pollastri with:
Gianluca Pollastri Ireland
Mona Singh United States
Sándor Pongor Italy
Thérèse E. Malliavin France
Phasit Charoenkwan Thailand
Alexander Rives United States
Tom Sercu United States
Hui Ding China
Alexander Rose Germany
Séan O’Donoghue Australia
Amarda Shehu relative to Gianluca Pollastri Ireland Gianluca Pollastri's profile →
Citations per field
00.5×1.6×
Gianluca Pollastri · 1×
Citations per year

Countries citing papers authored by Amarda Shehu

Since Specialization
Citations

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

Fields of papers citing papers by Amarda Shehu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amarda Shehu

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 7
5 3
6 3
7 1
8 3
9 2
10 2
11 27
12 2
13 2
14 3
15 3
16 160
17 46
18
Menthol Inhibits 5-HT3 Receptor–Mediated Currents
0
19 18
20 32

About Amarda Shehu

Amarda Shehu is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry, having authored 149 papers that have together received 2.3k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (104 papers), Enzyme Structure and Function (41 papers) and Machine Learning in Bioinformatics (35 papers). The work is most often cited by research in Microbiology (342 citations), Molecular Biology (1.9k citations) and Computational Theory and Mathematics (297 citations). Amarda Shehu has collaborated with scholars based in United States, Israel and Spain. Frequent co-authors include Uday Kamath, Daniel Veltri, Brian Olson, Lydia E. Kavraki, Kevin Molloy, Cecilia Clementi, Kenneth De Jong, Ruth Nussinov, Buyong Ma and Erion Plaku. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Bioinformatics.

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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