Indian Chronobiology Research packs in much diversity. It spans across timescales of cell division to daily physiological and behavioural rhythms.
Leading chronobiology research laboratories across the country
Prof. Sheeba Vasu
Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore
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Dr. Nisha N Kannan
Indian Institute of Science Education and Research (IISER), Thiruvananthapuram
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Dr. Sandipan Ray
Indian Institute of Technology Hyderabad
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Dr. Sanjay Kumar Bhardwaj
Chaudhary Charan Singh University, Meerut
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Dr. Ashutosh Srivastava
Indian Institute of Technology Gandhinagar
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Dr. Shaon Chakrabarti
National Centre for Biological Sciences (NCBS)
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Dr. Shahnaz Rahman Lone
GITAM School of Science, Visakhapatnam
Visit WebsiteLeading journals publishing chronobiology research
Research article dealing with circadian rhythms in living organisms
Visit JournalCovers broad range of biological rhythms such as ultradian, infradian, circadian or annual rhythms
Visit JournalMultidisciplinary journal that frequently publishes chronobiology studies
Visit JournalSoftware and tools for analyzing chronobiological data
Developed by Benjamin Schmid, Charlotte Helfrich-Förster, Taishi Yoshii. Used for analysis and visualization of chronobiological data.
Developed by Abhilash Lakshman & Sheeba Vasu.
Used for analysing circadian rhythms, to extract period and phase and other key characteristics.
Developed by Stanford Software Systems, Santa Cruz, California, USA (Refinetti et al., 2007).
Developed by Roelof Hut, University of Groningen, Netherlands. Software package for detecting and analyzing circadian and seasonal rhythms using harmonic regression and waveform fitting techniques.
Three Shiny apps CIRCADA-I, CIRCADA-E, and CIRCADA-S support exploration of circadian data, enabling visualization and analysis of circadian parameters like period and phase.
Brooks et al., 2021. Analyse time-series, high-throughput data to detect, quantify, and compare rhythms and circadian behaviour.
Ghosh & Sheeba, 2022. Collection of useful tools to visualize and analyze time series data obtained from Drosophila Activity Monitors.
Multiscale Oscillatory Dynamics Analysis. Designed for analysing real-life time-series data.
Non-parametric rhythm detection in large, genome-scale data sets and estimate their period length, phase, and amplitude.
Uses non-parametric methods to detect rhythms in time series data.
Python package for identifying periodic expression profiles in analysing circadian microarray data.
Persistent homology-based rhythm detection.
Detects rhythmic signals from large-scale time-series data. Combines ARSER, JTK_CYCLE and Lomb-Scargle.
R package used for statistical analyses and comparison of two circadian rhythms.
Differential RhythmicityY. R package used for assessing differential rhythmicity of a time series with two and more conditions.
Finds features with altered circadian rhythm parameters (amplitude and phase) between the control and experimental groups.
Used for estimation and prediction of a mixed-effects cosinor model for longitudinal periodic data.
Linear models for rhythmicity, design. Enables differential analysis of circadian transcriptome data.
Suite of packages that allows for identification and analysis of rhythms with changing amplitudes. Has three main components ECHO, ENCORE and MOSAIC.
Provides code for processing colour-switching Per2iLuc data in a high-throughput manner.
A widely used program for analysis of circadian rhythms.
The Chronobiologist's program.
Ametris' legacy data processing software, developed to capture objective, continuous data to inform measures of physical activity, sleep and vital signs.
Provides analysis functions for sleep, circadian rhythms and physical activity alongside device and data management tools.
Python package for actigraphy and light exposure data visualization and analysis.
Under development. Import, analyze and visualize wearable light logger data.
Visualization and analysis of data collected by HOBO environmental data loggers (temperature, light, humidity etc.).
Dim-light melatonin onset estimation.
Resources for accessing and analyzing chronobiology data
International societies advancing chronobiology research
Essential reading in chronobiology
Dunlap, J. C., Loros, J. J., & DeCoursey, P. J. (2004). Sinauer Associates.
Refinetti, R. (2016). CRC Press.
Koukkari, W. L., & Sothern, R. B. (2006). Springer Netherlands.
Kumar, V. (Ed.). (2017). Springer.
Kreitzman, L., & Foster, R. (2011). Profile Books.
Shackelford, J. (2022). University of Pittsburgh Press.
Shackelford, J. (2022). University of Pittsburgh Press.
Gander, P. (2023). Auckland University Press.
Rappole, J. H. (2013). Columbia University Press.
Foster, R., & Kreitzman, L. (2017). Oxford University Press.
Roenneberg, T. (2012). Harvard University Press.
Hut, R. A., & Schwartz, W. (2025).
Brown, S. A. (Ed.). (2021). Humana Press.
Cirelli, C. (Ed.). (2025). Oxford University Press.
Latest research contributions from Indian chronobiologists
1. Gopalakrishnan S, Nishad A, Regi R, Frost A, Yoshii T, Kannan NN. The curious case of CCHamide1: a role for CCHamide1 in sleep, metabolism, and fitness in Drosophila melanogaster. Genetics. 2026 Jun 3;233(2):iyag096. doi: 10.1093/genetics/iyag096. PMID: 41968725.
2. Geo Anna, Namitha Tharayil Jayalal, Anagha Jayan, Akash Ranjan Mishra, Nisha N Kannan, Circadian locomotor activity-rest rhythm in Drosophila is regulated by microRNA-275, Genetics, Volume 232, Issue 4, April 2026, iyag030, https://doi.org/10.1093/genetics/iyag030
3. Segu A, Sansaria S, Kannan NN. Tequila, the Serine Protease, Is Involved in Sleep-Dependent Memory Consolidation in Drosophila. eNeuro. 2025 Aug 28;12(8):ENEURO.0566-24.2025. doi: 10.1523/ENEURO.0566-24.2025. PMID: 40816727; PMCID: PMC12501825.
4. Sharma A, Rao S, Manjithaya R, Sheeba V. Differential response of neurons to autophagy modulation in Huntington's disease. Autophagy Rep. 2025 Jun 30;4(1):2519102. doi: 10.1080/27694127.2025.2519102. PMID: 40607262; PMCID: PMC12218432.
5. Naaz, Huda & Malik, Shalie & Rani, Sangeeta & Kumar, Sudhir. (2026). Sun-orientation behaviour and perching spacing in Common Myna (Acridotheres tristis) during morning and evening. International Journal of Zoology Studies. 11. 86-90.