Nitin Nair

3.6k total citations · 1 hit paper
39 papers, 1.0k citations indexed

About

Nitin Nair is a scholar working on Pharmacology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Nitin Nair has authored 39 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pharmacology, 7 papers in Molecular Biology and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Nitin Nair's work include Antibiotics Pharmacokinetics and Efficacy (8 papers), Cystic Fibrosis Research Advances (6 papers) and Lysosomal Storage Disorders Research (5 papers). Nitin Nair is often cited by papers focused on Antibiotics Pharmacokinetics and Efficacy (8 papers), Cystic Fibrosis Research Advances (6 papers) and Lysosomal Storage Disorders Research (5 papers). Nitin Nair collaborates with scholars based in United States, India and United Kingdom. Nitin Nair's co-authors include Julie Lekstrom-Himes, Steven M. Rowe, Cori Daines, C Simard, Felix C. Ringshausen, Elizabeth Tullis, Eitan Kerem, John Wilson, Edward P. Ingenito and Charlotte McKee and has published in prestigious journals such as New England Journal of Medicine, Neurology and Journal of Allergy and Clinical Immunology.

In The Last Decade

Nitin Nair

37 papers receiving 977 citations

Hit Papers

Tezacaftor–Ivacaftor in Residual-Function Heterozygotes w... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nitin Nair United States 15 373 268 165 129 88 39 1.0k
Chin‐Chen Chang Taiwan 22 188 0.5× 176 0.7× 78 0.5× 234 1.8× 41 0.5× 120 1.8k
Satoshi Shoji Japan 22 151 0.4× 185 0.7× 130 0.8× 542 4.2× 90 1.0× 115 1.7k
Jonathan Baker United Kingdom 18 444 1.2× 304 1.1× 200 1.2× 460 3.6× 21 0.2× 61 1.4k
Hang Chen China 18 200 0.5× 316 1.2× 172 1.0× 315 2.4× 21 0.2× 122 1.6k
Gan Chen China 21 234 0.6× 86 0.3× 133 0.8× 399 3.1× 75 0.9× 114 1.6k
Martin Schönfelder Germany 24 197 0.5× 265 1.0× 59 0.4× 369 2.9× 49 0.6× 91 1.3k
Chris I. Jones United Kingdom 25 400 1.1× 130 0.5× 164 1.0× 385 3.0× 54 0.6× 58 1.7k
Min Ho Lee South Korea 20 222 0.6× 65 0.2× 255 1.5× 125 1.0× 165 1.9× 111 1.4k
Marcelo E. Andía Chile 25 350 0.9× 110 0.4× 152 0.9× 337 2.6× 18 0.2× 91 1.8k

Countries citing papers authored by Nitin Nair

Since Specialization
Citations

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

Fields of papers citing papers by Nitin Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nitin Nair

This figure shows the co-authorship network connecting the top 25 collaborators of Nitin Nair. A scholar is included among the top collaborators of Nitin 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 Nitin Nair. Nitin Nair 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
1.
Zemanick, Edith T., Bonnie W. Ramsey, Dorota Sands, et al.. (2025). Sweat chloride reflects CFTR function and correlates with clinical outcomes following CFTR modulator treatment. Journal of Cystic Fibrosis. 24(2). 246–254. 6 indexed citations
2.
Montgomery, Sean M., Nitin Nair, Yi‐Ping Phoebe Chen, & Suzanne Dikker. (2023). Introducing EmotiBit, an open-source multi-modal sensor for measuring research-grade physiological signals. Science Talks. 6. 100181–100181. 15 indexed citations
3.
Nair, Nitin, Orlando Aristizábal, Jonathan Mamou, et al.. (2021). A Deep Learning Approach for Segmentation, Classification, and Visualization of 3-D High-Frequency Ultrasound Images of Mouse Embryos. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 68(7). 2460–2471. 11 indexed citations
4.
Nair, Nitin, Orlando Aristizábal, Jonathan Mamou, et al.. (2020). Deep Mouse: An End-to-End Auto-Context Refinement Framework for Brain Ventricle & Body Segmentation in Embryonic Mice Ultrasound Volumes. PubMed. 2020. 122–126. 9 indexed citations
5.
Nair, Nitin, Orlando Aristizábal, Jonathan Mamou, et al.. (2018). Deep Bv: A Fully Automated System for Brain Ventricle Localization and Segmentation In 3D Ultrasound Images of Embryonic Mice. PubMed. 15. 1–6. 9 indexed citations
7.
Nair, Nitin, et al.. (2018). Predicting Engagement Intensity in the Wild Using Temporal Convolutional Network. 604–610. 31 indexed citations
9.
Rowe, Steven M., Cori Daines, Felix C. Ringshausen, et al.. (2017). Tezacaftor–Ivacaftor in Residual-Function Heterozygotes with Cystic Fibrosis. New England Journal of Medicine. 377(21). 2024–2035. 364 indexed citations breakdown →
10.
Jones, Simon, Catherine Breen, Stewart Rust, et al.. (2016). A phase 1/2 study of intrathecal heparan-N-sulfatase in patients with mucopolysaccharidosis IIIA. Molecular Genetics and Metabolism. 118(3). 198–205. 83 indexed citations
11.
Shapiro, Elsa, Igor Nestrašil, Kathleen Delaney, et al.. (2016). A Prospective Natural History Study of Mucopolysaccharidosis Type IIIA. The Journal of Pediatrics. 170. 278–287.e4. 90 indexed citations
12.
Konstan, Michael W., Bonnie W. Ramsey, J.S. Elborn, et al.. (2015). Safety and efficacy of treatment with Lumacaftor in combination with Ivacaftor in patients with Cf homozygous for F508Del-Cftr. Pediatric Pulmonology. 50. 269–270. 1 indexed citations
13.
Dubey, Akhilesh, et al.. (2015). DEVELOPMENT AND INVESTIGATION OF TIMOLOL MALEATE AND LATANOPROST COMBINATION LIPOSOMES FOR THE TREATMENT OF GLAUCOMA. International Research Journal of Pharmacy. 6(4). 256–264. 5 indexed citations
14.
Schiffmann, Raphael, Markus Ries, Derek Blankenship, et al.. (2013). Changes in plasma and urine globotriaosylceramide levels do not predict Fabry disease progression over 1 year of agalsidase alfa. Genetics in Medicine. 15(12). 983–989. 24 indexed citations
15.
Nair, Nitin, et al.. (2013). Effect of Siloxanes Contained in Natural Gas on the Operation of a Residential Furnace. Industrial & Engineering Chemistry Research. 52(18). 6253–6261. 21 indexed citations
16.
Nair, Nitin, et al.. (2000). Direct drug susceptibility test for tubercle bacilli by the sputum swab culture method.. PubMed. 4(2). 168–73. 1 indexed citations
17.
Immanuel, Chandra, et al.. (1974). A modified method for the estimation of acetylisoniazid in urine.. PubMed. 62(6). 945–52. 11 indexed citations
18.
Venkataraman, P, et al.. (1972). Classification of subjects as slow or rapid inactivators of isoniazid, based on the ratio of the urinary excretion of acetylisoniazid to isoniazid.. PubMed. 60(5). 685–93. 3 indexed citations
19.
Mitchison, D A, et al.. (1970). Sulphadimidine Acetylation Test for Classification of Patients as Slow or Rapid Inactivators of Isoniazid. BMJ. 3(5721). 495–497. 51 indexed citations
20.
Kailasam, S., et al.. (1968). A simple qualitative test for deterioration of cycloserine.. PubMed. 39(5). 842–4. 1 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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