Chandran Nithin

1.2k total citations
26 papers, 675 citations indexed

About

Chandran Nithin is a scholar working on Molecular Biology, Materials Chemistry and Plant Science. According to data from OpenAlex, Chandran Nithin has authored 26 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 5 papers in Materials Chemistry and 4 papers in Plant Science. Recurrent topics in Chandran Nithin's work include RNA and protein synthesis mechanisms (17 papers), RNA modifications and cancer (11 papers) and RNA Research and Splicing (9 papers). Chandran Nithin is often cited by papers focused on RNA and protein synthesis mechanisms (17 papers), RNA modifications and cancer (11 papers) and RNA Research and Splicing (9 papers). Chandran Nithin collaborates with scholars based in Poland, India and Netherlands. Chandran Nithin's co-authors include Janusz M. Bujnicki, Ranjit Prasad Bahadur, Sunandan Mukherjee, Jolly Basak, Pritha Ghosh, Almudena Ponce-Salvatierra, Tomasz Wirecki, Eric J. Snijder, Martijn J. van Hemert and Danny Incarnato and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Cellular and Molecular Life Sciences.

In The Last Decade

Chandran Nithin

25 papers receiving 672 citations

Peers

Chandran Nithin

ECOLO

Pascal Rigolet France

Mark A. Boerneke United States

Jennifer T. Miller United States

Jagat Adhikari United States

Mathilde Lethier France

Grzegorz Chojnowski Germany

Joshua D. Jones United States

Migle Kazlauskiene Lithuania

Gajinder Pal Singh India

Pascal Rigolet France

Chandran Nithin

361 ×0.6

48 ×0.5

80 ×0.9

21 ×0.4

ECOLO

33 ×0.8

Citations per year, relative to Chandran Nithin Chandran Nithin (= 1×) peers Pascal Rigolet

Countries citing papers authored by Chandran Nithin

Since Specialization

Citations

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

Fields of papers citing papers by Chandran Nithin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chandran Nithin

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

All Works

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20 of 20 papers shown

Li, Hao, Chandran Nithin, Sebastian Kmiecik, & Sheng‐You Huang. (2025). Computational methods for modeling protein–protein interactions in the AI era: Current status and future directions. Drug Discovery Today. 30(6). 104382–104382. 1 indexed citations

Nithin, Chandran, et al.. (2025). When does molecular dynamics improve RNA models? Insights from CASP15 and practical guidelines. Computational and Structural Biotechnology Journal. 27. 4201–4211. 1 indexed citations

Nithin, Chandran, et al.. (2025). Protein‐ RNA Docking Benchmark v3.0 Integrated With Binding Affinity. Proteins Structure Function and Bioinformatics. 93(9). 1534–1552.

Ghosh, Pritha, Chandran Nithin, Daniela Strauß, et al.. (2022). Molecular insights into RNA recognition and gene regulation by the TRIM-NHL protein Mei-P26. Life Science Alliance. 5(8). e202201418–e202201418. 2 indexed citations

Nithin, Chandran, Sunandan Mukherjee, Jolly Basak, & Ranjit Prasad Bahadur. (2022). NCodR: A multi-class support vector machine classification to distinguish non-coding RNAs in Viridiplantae. SHILAP Revista de lepidopterología. 3. e23–e23. 3 indexed citations

Koralewska, Natalia, Dorota Gudanis, Daniel Baranowski, et al.. (2021). RNA and DNA G-quadruplexes bind to human dicer and inhibit its activity. Cellular and Molecular Life Sciences. 78(7). 3709–3724. 15 indexed citations

Neubacher, Saskia, Chandran Nithin, Sunandan Mukherjee, et al.. (2021). Constrained peptides mimic a viral suppressor of RNA silencing. Nucleic Acids Research. 49(22). 12622–12633. 15 indexed citations

Nithin, Chandran, Almudena Ponce-Salvatierra, Pritha Ghosh, et al.. (2020). Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements. Nucleic Acids Research. 48(22). 12436–12452. 189 indexed citations

Wirecki, Tomasz, Chandran Nithin, Sunandan Mukherjee, Janusz M. Bujnicki, & M. Boniecki. (2020). Modeling of Three-Dimensional RNA Structures Using SimRNA. Methods in molecular biology. 2165. 103–125. 16 indexed citations

10.

Ponce-Salvatierra, Almudena, et al.. (2019). Computational modeling of RNA 3D structure based on experimental data. Bioscience Reports. 39(2). 31 indexed citations

11.

Nithin, Chandran, Sunandan Mukherjee, & Ranjit Prasad Bahadur. (2019). A structure-based model for the prediction of protein–RNA binding affinity. RNA. 25(12). 1628–1645. 11 indexed citations

12.

Mukherjee, Sunandan, et al.. (2019). QRNAS: software tool for refinement of nucleic acid structures. BMC Structural Biology. 19(1). 5–5. 58 indexed citations

13.

Nithin, Chandran, et al.. (2018). Identification and characterization of differentially expressed Phaseolus vulgaris miRNAs and their targets during mungbean yellow mosaic India virus infection reveals new insight into Phaseolus-MYMIV interaction. Genomics. 111(6). 1333–1342. 11 indexed citations

14.

Nithin, Chandran, Sunandan Mukherjee, & Ranjit Prasad Bahadur. (2016). A non-redundant protein-RNA docking benchmark version 2.0. Proteins Structure Function and Bioinformatics. 85(2). 256–267. 27 indexed citations

15.

Nithin, Chandran, et al.. (2015). Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures. BMC Plant Biology. 15(1). 140–140. 26 indexed citations

16.

Nithin, Chandran, et al.. (2015). Molecular architecture of protein-RNA recognition sites. Journal of Biomolecular Structure and Dynamics. 33(12). 2738–2751. 37 indexed citations

17.

Nithin, Chandran, et al.. (2015). Probing binding hot spots at protein–RNA recognition sites. Nucleic Acids Research. 44(2). e9–e9. 37 indexed citations

18.

Basak, Jolly & Chandran Nithin. (2015). Targeting Non-Coding RNAs in Plants with the CRISPR-Cas Technology is a Challenge yet Worth Accepting. Frontiers in Plant Science. 6. 1001–1001. 41 indexed citations

19.

Nithin, Chandran, et al.. (2012). A protein–RNA docking benchmark (I): Nonredundant cases. Proteins Structure Function and Bioinformatics. 80(7). 1866–1871. 36 indexed citations

20.

Nithin, Chandran, et al.. (2011). Designing and development of novel antituberculosis drugs by in silico targeting against Decaprenyl-phosphoryl-β-D-ribose oxidase: A structure based drug designing approach. Journal of Natural Science Biology and Medicine. 2(3). 72. 2 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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