Ava P. Amini

1.1k citations
12 papers · 277 indexed · 2 hit papers · h-index 6
Topics
Machine Learning in Bioinformatics (4 papers)Protein Structure and Dynamics (4 papers)Single-cell and spatial transcriptomics (3 papers)

In The Last Decade

Ava P. Amini

11 papers receiving 266 citations

Hit Papers

Protein structure generation via folding diffusion20242026202520242025255075

Peers

Ava P. Amini
Comparison fields: 5 of 77
  • Molecular Biology 124
  • Artificial Intelligence 64
  • Computer Vision and Pattern Recognition 43
  • Safety Research 32
  • Materials Chemistry 27
Replace Zan Armstrong with:
Zan Armstrong United States
Andrew McNutt United States
R. Clyde White United Kingdom
Gamze Gürsoy United States
Shiori Sagawa United States
Hongbin Ye China
Po‐Ting Lai Taiwan
Md Momin Al Aziz Canada
Pascal Berrang Germany
Diyue Bu United States
Ava P. Amini relative to Zan Armstrong United States Zan Armstrong's profile →
Citations per field
00.5×11×
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Citations per year

Countries citing papers authored by Ava P. Amini

Since Specialization
Citations

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

Fields of papers citing papers by Ava P. Amini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ava P. Amini. 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 Ava P. Amini. The network helps show where Ava P. Amini may publish in the future.

Co-authorship network of co-authors of Ava P. Amini

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 1
2 0
3 3
4 1
5
Zero-shot evaluation reveals limitations of single-cell foundation modelsbreakdown →
18
6 3
7
Protein structure generation via folding diffusionbreakdown →
76
8 9
9 25
10 32
11 1
12 108

About Ava P. Amini

Ava P. Amini is a scholar working on Biophysics, Molecular Biology and Computational Theory and Mathematics, having authored 12 papers that have together received 277 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (4 papers), Protein Structure and Dynamics (4 papers) and Single-cell and spatial transcriptomics (3 papers). The work is most often cited by research in Health Informatics (15 citations), Safety Research (32 citations) and Computer Vision and Pattern Recognition (43 citations). Ava P. Amini has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Sangeeta N. Bhatia, Wilko Schwarting, Daniela Rus, Ava P. Soleimany, Kevin Yang, Alex X. Lu, Sarah Alamdari, James Zou, Rianne van den Berg and Kevin Wu. Their work appears in journals such as Cell, Nature Communications 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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