Sanjeev Khosla

1.5k total citations
34 papers, 1.1k citations indexed

About

Sanjeev Khosla is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Sanjeev Khosla has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 15 papers in Genetics and 5 papers in Infectious Diseases. Recurrent topics in Sanjeev Khosla's work include Epigenetics and DNA Methylation (18 papers), RNA modifications and cancer (9 papers) and Genetic Syndromes and Imprinting (8 papers). Sanjeev Khosla is often cited by papers focused on Epigenetics and DNA Methylation (18 papers), RNA modifications and cancer (9 papers) and Genetic Syndromes and Imprinting (8 papers). Sanjeev Khosla collaborates with scholars based in India, United Kingdom and Japan. Sanjeev Khosla's co-authors include Vinay Kumar Nandicoori, Gokul Gopinathan, Imtiyaz Yaseen, Richard I. Gregory, Gayatri Ramakrishna, Robert Feil, Prabhjot Kaur, Vani Brahmachari, Sandeep Upadhyay and Devi Thiagarajan and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The EMBO Journal.

In The Last Decade

Sanjeev Khosla

33 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sanjeev Khosla India 19 782 330 189 152 122 34 1.1k
Todd A. Gray United States 24 1.4k 1.8× 760 2.3× 338 1.8× 334 2.2× 249 2.0× 38 1.9k
Lawrence Bechtel United States 9 327 0.4× 184 0.6× 133 0.7× 76 0.5× 47 0.4× 10 805
Jacek Kowalski Poland 19 299 0.4× 124 0.4× 87 0.5× 254 1.7× 117 1.0× 64 985
Jacob Souopgui Belgium 17 732 0.9× 110 0.3× 289 1.5× 71 0.5× 30 0.2× 61 1.2k
Zuyong He China 21 810 1.0× 417 1.3× 175 0.9× 74 0.5× 30 0.2× 77 1.4k
Fang Fu China 17 253 0.3× 506 1.5× 445 2.4× 114 0.8× 149 1.2× 66 1.1k
Chetankumar S. Tailor United States 15 435 0.6× 395 1.2× 108 0.6× 167 1.1× 52 0.4× 20 963
Kimberly Ferguson United States 11 594 0.8× 287 0.9× 238 1.3× 49 0.3× 26 0.2× 11 1.3k
R. Thomas Taggart United States 12 508 0.6× 140 0.4× 59 0.3× 78 0.5× 40 0.3× 21 791
Graham Speight Australia 17 401 0.5× 151 0.5× 360 1.9× 180 1.2× 21 0.2× 28 1.2k

Countries citing papers authored by Sanjeev Khosla

Since Specialization
Citations

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

Fields of papers citing papers by Sanjeev Khosla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanjeev Khosla

This figure shows the co-authorship network connecting the top 25 collaborators of Sanjeev Khosla. A scholar is included among the top collaborators of Sanjeev Khosla 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 Sanjeev Khosla. Sanjeev Khosla 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.
Sharma, Ankita, Sahanawaz Molla, Amit Tuli, et al.. (2025). Fundamental role of spatial positioning of Mycobacterium tuberculosis in mycobacterial survival in macrophages. Nature Communications. 16(1). 9368–9368.
2.
Khosla, Sanjeev, et al.. (2023). The Mycobacterium tuberculosis methyltransferase Rv2067c manipulates host epigenetic programming to promote its own survival. Nature Communications. 14(1). 8497–8497. 8 indexed citations
3.
Khosla, Sanjeev, et al.. (2018). Biochemical and dynamic basis for combinatorial recognition of H3R2K9me2 by dual domains of UHRF1. Biochimie. 149. 105–114. 6 indexed citations
4.
Sen, Bijoya, et al.. (2017). Differentially regulated gene expression in quiescence versus senescence and identification of ARID5A as a quiescence associated marker. Journal of Cellular Physiology. 233(5). 3695–3712. 8 indexed citations
5.
Yaseen, Imtiyaz, et al.. (2017). Histone methyltransferase SUV 39H1 participates in host defense by methylating mycobacterial histone‐like protein HupB. The EMBO Journal. 37(2). 183–200. 25 indexed citations
6.
Sharma, Garima, Divya Tej Sowpati, Mehak Zahoor Khan, et al.. (2016). Genome-wide non-CpG methylation of the host genome during M. tuberculosis infection. Scientific Reports. 6(1). 25006–25006. 41 indexed citations
7.
Yaseen, Imtiyaz, Prabhjot Kaur, Vinay Kumar Nandicoori, & Sanjeev Khosla. (2015). Mycobacteria modulate host epigenetic machinery by Rv1988 methylation of a non-tail arginine of histone H3. Nature Communications. 6(1). 8922–8922. 114 indexed citations
8.
Mishra, Rakesh K., et al.. (2014). The CpG Island Encompassing the Promoter and First Exon of Human DNMT3L Gene Is a PcG/TrX Response Element (PRE). PLoS ONE. 9(4). e93561–e93561. 11 indexed citations
9.
Gopinathan, Gokul & Sanjeev Khosla. (2012). DNA Methylation and Cancer. Sub-cellular biochemistry. 61. 597–625. 58 indexed citations
10.
Thiagarajan, Devi, et al.. (2011). The DNA methyltranferase Dnmt2 participates in RNA processing during cellular stress. Epigenetics. 6(1). 103–113. 60 indexed citations
11.
Singh, Narendra Pratap, Surabhi Srivastava, Senthilkumar Ramamoorthy, et al.. (2011). Epigenetic profile of the euchromatic region of human Y chromosome. Nucleic Acids Research. 39(9). 3594–3606. 16 indexed citations
12.
Gopinathan, Gokul, Gayatri Ramakrishna, & Sanjeev Khosla. (2009). Reprogramming of HeLa cells upon DNMT3L overexpression mimics carcinogenesis. Epigenetics. 4(5). 322–329. 19 indexed citations
13.
Khare, Garima, et al.. (2009). A novel nucleoid-associated protein of Mycobacterium tuberculosis is a sequence homolog of GroEL. Nucleic Acids Research. 37(15). 4944–4954. 50 indexed citations
14.
Sowpati, Divya Tej, Devi Thiagarajan, Sudhish Sharma, et al.. (2008). An intronic DNA sequence within the mouse Neuronatin gene exhibits biochemical characteristics of an ICR and acts as a transcriptional activator in Drosophila. Mechanisms of Development. 125(11-12). 963–973. 7 indexed citations
15.
Gautami, Bhimana, et al.. (2007). DNA Methylation Profile at the DNMT3L Promoter: A Potential Biomarker for Cervical Cancer. Epigenetics. 2(2). 80–85. 39 indexed citations
16.
Khosla, Sanjeev, Geetu Mendiratta, & Vani Brahmachari. (2006). Genomic imprinting in the mealybugs. Cytogenetic and Genome Research. 113(1-4). 41–52. 39 indexed citations
17.
Gregory, Richard I., Sanjeev Khosla, & Robert Feil. (2002). Probing Chromatin Structure with Nuclease Sensitivity Assays. Humana Press eBooks. 181. 269–284. 5 indexed citations
18.
John, Rosalind M., Samuel Aparício, Justin Ainscough, et al.. (2001). Imprinted Expression of Neuronatin from Modified BAC Transgenes Reveals Regulation by Distinct and Distant Enhancers. Developmental Biology. 236(2). 387–399. 51 indexed citations
19.
Khosla, Sanjeev, Meena Augustus, & Vani Brahmachari. (1999). Sex-specific organisation of middle repetitive DNA sequences in the mealybug Planococcus lilacinus. Nucleic Acids Research. 27(18). 3745–3751. 16 indexed citations
20.
Khosla, Sanjeev, et al.. (1996). A male-specific nuclease-resistant chromatin fraction in the mealybug Planococcus lilacinus. Chromosoma. 104(5). 386–392. 20 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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