Arian R. Jamasb

1.5k total citations · 2 hit papers
10 papers, 595 citations indexed

About

Arian R. Jamasb is a scholar working on Computational Theory and Mathematics, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Arian R. Jamasb has authored 10 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 5 papers in Molecular Biology and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Arian R. Jamasb's work include Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (3 papers) and Neurobiology and Insect Physiology Research (3 papers). Arian R. Jamasb is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (3 papers) and Neurobiology and Insect Physiology Research (3 papers). Arian R. Jamasb collaborates with scholars based in United Kingdom, United States and Switzerland. Arian R. Jamasb's co-authors include Tom L. Blundell, Michael M. Bronstein, Ben Day, Píetro Lió, Alexander Shakeel Bates, Gregory S.X.E. Jefferis, Davi D. Bock, Esteban J. Beckwith, Quentin Geissmann and Jake P. Taylor‐King and has published in prestigious journals such as Current Biology, PLoS Biology and Chemical Science.

In The Last Decade

Arian R. Jamasb

10 papers receiving 585 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine learning-aided generative molecular design

2024 68 citations Yuanqi Du, Arian R. Jamasb et al. Nature Machine Intelligence profile →
Structure-based drug design with equivariant diffusion models

2024 52 citations Arne Schneuing, Charles B. Harris et al. Nature Computational Science profile →

Peers

Arian R. Jamasb

CMN

MB

CTM

MC

GENET

Ron Davis United States

Ping Luo China

Pablo Mier Germany

Denis Dupuy France

Katja Luck Germany

Makiko Suwa Japan

Ludovica Montanucci Italy

Zhidong Xue China

Victor Neduva Germany

Wenze Li United States

Ron Davis United States

Arian R. Jamasb

123 ×0.6

CMN

584 ×3.2

MB

54 ×0.3

CTM

54 ×0.5

MC

83 ×0.7

GENET

Citations per year, relative to Arian R. Jamasb Arian R. Jamasb (= 1×) peers Ron Davis

Countries citing papers authored by Arian R. Jamasb

Since Specialization

Citations

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

Fields of papers citing papers by Arian R. Jamasb

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arian R. Jamasb. 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 Arian R. Jamasb. The network helps show where Arian R. Jamasb may publish in the future.

Co-authorship network of co-authors of Arian R. Jamasb

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Schneuing, Arne, Charles B. Harris, Yuanqi Du, et al.. (2024). Structure-based drug design with equivariant diffusion models. Nature Computational Science. 4(12). 899–909. 52 indexed citations breakdown →

2.

Du, Yuanqi, Arian R. Jamasb, Jeff Guo, et al.. (2024). Machine learning-aided generative molecular design. Nature Machine Intelligence. 6(6). 589–604. 68 indexed citations breakdown →

3.

Griffiths, Ryan‐Rhys, Jake L. Greenfield, Aditya R. Thawani, et al.. (2022). Data-driven discovery of molecular photoswitches with multioutput Gaussian processes. Chemical Science. 13(45). 13541–13551. 28 indexed citations

4.

Jamasb, Arian R., Ben Day, Cătălina Cangea, Píetro Lió, & Tom L. Blundell. (2021). Deep Learning for Protein–Protein Interaction Site Prediction. Methods in molecular biology. 2361. 263–288. 12 indexed citations

5.

Beaudoin, Christopher A., Arian R. Jamasb, Andries J. van Tonder, et al.. (2021). Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses. Computational and Structural Biotechnology Journal. 19. 3938–3953. 26 indexed citations

6.

Day, Ben, Arian R. Jamasb, Jyothish Soman, et al.. (2021). Utilizing graph machine learning within drug discovery and development. Briefings in Bioinformatics. 22(6). 154 indexed citations

7.

Bates, Alexander Shakeel, Philipp Schlegel, Ruairí J.V. Roberts, et al.. (2020). Complete Connectomic Reconstruction of Olfactory Projection Neurons in the Fly Brain. Current Biology. 30(16). 3183–3199.e6. 106 indexed citations

8.

Thomas, S.E., Arian R. Jamasb, Christopher A. Beaudoin, et al.. (2020). SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets. Briefings in Bioinformatics. 22(2). 769–780. 29 indexed citations

9.

Frechter, Shahar, Alexander Shakeel Bates, Sina Tootoonian, et al.. (2019). Functional and anatomical specificity in a higher olfactory centre. eLife. 8. 55 indexed citations

10.

Geissmann, Quentin, Luis García Rodríguez, Esteban J. Beckwith, et al.. (2017). Ethoscopes: An open platform for high-throughput ethomics. PLoS Biology. 15(10). e2003026–e2003026. 65 indexed citations

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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