Pooja Kathail

2.7k total citations · 2 hit papers
7 papers, 1.4k citations indexed

About

Pooja Kathail is a scholar working on Molecular Biology, Genetics and Nephrology. According to data from OpenAlex, Pooja Kathail has authored 7 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Nephrology. Recurrent topics in Pooja Kathail's work include Single-cell and spatial transcriptomics (4 papers), Gene Regulatory Network Analysis (4 papers) and Epigenetics and DNA Methylation (2 papers). Pooja Kathail is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), Gene Regulatory Network Analysis (4 papers) and Epigenetics and DNA Methylation (2 papers). Pooja Kathail collaborates with scholars based in United States, Australia and Lithuania. Pooja Kathail's co-authors include Dana Pe’er, Cassandra Burdziak, Kevin R. Moon, Linas Mažutis, Guy Wolf, Kristina Yim, Brian Bierie, Diwakar R. Pattabiraman, Christine L. Chaffer and Ambrose Carr and has published in prestigious journals such as Cell, Nature Genetics and Nature Biotechnology.

In The Last Decade

Pooja Kathail

7 papers receiving 1.4k citations

Hit Papers

Recovering Gene Interactions from Single-Cell Data Using ... 2016 2026 2019 2022 2018 2016 250 500 750
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.

  1. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion
    2018 945 citations David van Dijk, Roshan Sharma et al. Cell profile →
  2. Wishbone identifies bifurcating developmental trajectories from single-cell data
    2016 384 citations Manu Setty, Michelle D. Tadmor et al. Nature Biotechnology profile →

Peers

Pooja Kathail
Adam Gayoso United States
Cassandra Burdziak United States
Kieran R. Campbell Canada
Lev Silberstein United States
Gustavo S. França Brazil
Delasa Aghamirzaie United States
Joseph Bergenstråhle Sweden
Livnat Jerby‐Arnon United States
Amanda Larson Gedman United States
Linnea Stenbeck Sweden
Adam Gayoso United States
Pooja Kathail
Citations per year, relative to Pooja Kathail Pooja Kathail (= 1×) peers Adam Gayoso

Countries citing papers authored by Pooja Kathail

Since Specialization
Citations

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

Fields of papers citing papers by Pooja Kathail

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pooja Kathail

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

All Works

7 of 7 papers shown
1.
Loeb, Gabriel B., Pooja Kathail, Richard W. Shuai, et al.. (2024). Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function. Nature Genetics. 56(10). 2078–2092. 3 indexed citations
2.
Kathail, Pooja, et al.. (2024). Current genomic deep learning models display decreased performance in cell type-specific accessible regions. Genome biology. 25(1). 202–202. 2 indexed citations
3.
Gordon, Max, et al.. (2024). Population Diversity at the Single-Cell Level. Annual Review of Genomics and Human Genetics. 25(1). 27–49. 1 indexed citations
4.
Huang, Connie, et al.. (2023). Personal transcriptome variation is poorly explained by current genomic deep learning models. Nature Genetics. 55(12). 2056–2059. 32 indexed citations
5.
Dijk, David van, Roshan Sharma, Juozas Nainys, et al.. (2018). Recovering Gene Interactions from Single-Cell Data Using Data Diffusion. Cell. 174(3). 716–729.e27. 945 indexed citations breakdown →
6.
Dijk, David van, Roshan Sharma, Kristina Yim, et al.. (2018). Recovering Gene Interactions from Single-Cell Data Using Data Diffusion. SSRN Electronic Journal. 10 indexed citations
7.
Setty, Manu, Michelle D. Tadmor, Shlomit Reich-Zeliger, et al.. (2016). Wishbone identifies bifurcating developmental trajectories from single-cell data. Nature Biotechnology. 34(6). 637–645. 384 indexed citations breakdown →

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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