Surag Nair

1.6k total citations
14 papers, 267 citations indexed

About

Surag Nair is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Surag Nair has authored 14 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 2 papers in Artificial Intelligence and 2 papers in Cancer Research. Recurrent topics in Surag Nair's work include Genomics and Chromatin Dynamics (5 papers), Genomics and Phylogenetic Studies (5 papers) and RNA and protein synthesis mechanisms (3 papers). Surag Nair is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), Genomics and Phylogenetic Studies (5 papers) and RNA and protein synthesis mechanisms (3 papers). Surag Nair collaborates with scholars based in United States, India and Taiwan. Surag Nair's co-authors include Anshul Kundaje, Avanti Shrikumar, Daniel Sunwook Kim, Georgi K. Marinov, Peyton Greenside, Anna Shcherbina, Jacob Schreiber, Rui Li, Anusri Pampari and Katerina Kraft and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Genetics.

In The Last Decade

Surag Nair

13 papers receiving 266 citations

Peers

Surag Nair
Lucas Seninge United States
Morteza Oladnabi Iran
Ruian Yang China
Andrian Yang Australia
Adam Richards United States
Emily Fabyanic United States
Jesús Eduardo Rojo Arias Germany
Shadi Shams United States
Federico López United Kingdom
Jianguo Rao United Kingdom
Lucas Seninge United States
Surag Nair
Citations per year, relative to Surag Nair Surag Nair (= 1×) peers Lucas Seninge

Countries citing papers authored by Surag Nair

Since Specialization
Citations

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

Fields of papers citing papers by Surag Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Surag Nair

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

All Works

14 of 14 papers shown
1.
Lal, Avantika, et al.. (2025). gReLU: a comprehensive framework for DNA sequence modeling and design. Nature Methods. 22(11). 2253–2257.
2.
Wang, Yu Xin, Adelaida R. Palla, Andrew Tri Van Ho, et al.. (2025). Multiomic profiling reveals that prostaglandin E2 reverses aged muscle stem cell dysfunction, leading to increased regeneration and strength. Cell stem cell. 32(7). 1154–1169.e9. 1 indexed citations
3.
Yeo, Robin W., Eric Sun, Paloma Navarro Negredo, et al.. (2023). Chromatin accessibility dynamics of neurogenic niche cells reveal defects in neural stem cell adhesion and migration during aging. Nature Aging. 3(7). 866–893. 14 indexed citations
4.
Nair, Surag, Avanti Shrikumar, Jacob Schreiber, & Anshul Kundaje. (2022). fastISM: performant in silico saturation mutagenesis for convolutional neural networks. Bioinformatics. 38(9). 2397–2403. 14 indexed citations
5.
Schreiber, Jacob, Surag Nair, Akshay Balsubramani, & Anshul Kundaje. (2022). Accelerating in silico saturation mutagenesis using compressed sensing. Bioinformatics. 38(14). 3557–3564. 4 indexed citations
6.
Nair, Surag, Daofeng Li, Brian J. Raney, et al.. (2022). The dynseq browser track shows context-specific features at nucleotide resolution. Nature Genetics. 54(11). 1581–1583. 3 indexed citations
7.
Ameen, Mohamed, Laksshman Sundaram, Mengcheng Shen, et al.. (2022). Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease. Cell. 185(26). 4937–4953.e23. 46 indexed citations
8.
Wang, Sean K., Surag Nair, Rui Li, et al.. (2022). Single-cell multiome of the human retina and deep learning nominate causal variants in complex eye diseases. Cell Genomics. 2(8). 100164–100164. 38 indexed citations
9.
Markov, Glenn J., Thach Mai, Surag Nair, et al.. (2021). AP-1 is a temporally regulated dual gatekeeper of reprogramming to pluripotency. Proceedings of the National Academy of Sciences. 118(23). 24 indexed citations
10.
Nair, Surag, et al.. (2019). Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts. Bioinformatics. 35(14). i108–i116. 41 indexed citations
11.
Greenside, Peyton, et al.. (2019). Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays. PLoS ONE. 14(6). e0218073–e0218073. 59 indexed citations
12.
Shrikumar, Avanti, Katherine Tian, Anna Shcherbina, et al.. (2018). TF-MoDISco v0.4.2.2-alpha: Technical Note. arXiv (Cornell University). 8 indexed citations
13.
Nair, Surag, et al.. (2018). The Big Win Strategy on Multi-Value Network. 78–81. 4 indexed citations
14.
Suri, Manan, et al.. (2015). Neuromorphic Hardware Accelerated Adaptive Authentication System. 3. 1206–1213. 11 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Lucas Seninge Breakdown of academic impact, for papers by Morteza Oladnabi Breakdown of academic impact, for papers by Ruian Yang Breakdown of academic impact, for papers by Andrian Yang Breakdown of academic impact, for papers by Adam Richards Breakdown of academic impact, for papers by Emily Fabyanic Breakdown of academic impact, for papers by Jesús Eduardo Rojo Arias Breakdown of academic impact, for papers by Shadi Shams Breakdown of academic impact, for papers by Federico López Breakdown of academic impact, for papers by Jianguo Rao
Rankless by CCL
2026