Building upon my extensive experience in computational biology, transcriptomics, proteomics, and modeling of gene regulatory networks, my research interest lies in leveraging integrative systems biology approaches to unravel the intricate mechanisms governing sleep and circadian rhythms. Specifically, I aim to elucidate the interplay between genetic, molecular, and physiological factors underlying sleep disorders and circadian dysregulation, with a focus on translational implications for clinical diagnosis and treatment.

• Multi-omics Integration: Integrating transcriptomics and proteomics data to elucidate comprehensive molecular signatures associated with sleep disorders such as Alzheimer's disease and obesity, aiming to identify biomarkers for early diagnosis and therapeutic targeting.

• Network Modeling of Circadian Systems: Expanding upon previous work in modeling gene regulatory networks of the mammalian circadian system, further incorporating dynamic interactions between morning and evening oscillators to elucidate mechanisms underlying circadian rhythm modulation and entrainment.

• Machine Learning for Sleep Patterns: Building upon the development of machine learning models for analyzing transcriptomics data to assess human physiological time, I propose the exploration of advanced machine learning techniques for high-resolution characterization of sleep patterns and their association with health outcomes.

• Computational Modeling of Neuronal Functionality: Leveraging stochastic modeling approaches to investigate circadian modulation of neuronal functionality and firing patterns within key brain regions such as the suprachiasmatic nucleus (SCN), aiming to uncover the neural circuits underlying sleep-wake regulation.

• Clinical Translation and Application: Translating findings from basic research into clinically relevant tools and strategies, such as the development of user-friendly software for analyzing sleep and circadian data, and integrating computational models into diagnostic and therapeutic approaches for sleep disorders.

• <p style="border: 0px solid rgb(227, 227, 227); box-sizing: border-box; --tw-border-spacing-x: 0; --tw-border-spacing-y: 0; --tw-translate-x: 0; --tw-translate-y: 0; --tw-rotate: 0; --tw-skew-x: 0; --tw-skew-y: 0; --tw-scale-x: 1; --tw-scale-y: 1; --tw-pan-x: ; --tw-pan-y: ; --tw-pinch-zoom: ; --tw-scroll-snap-strictness: proximity; --tw-gradient-from-position: ; --tw-gradient-via-position: ; --tw-gradient-to-position: ; --tw-ordinal: ; --tw-slashed-zero: ; --tw-numeric-figure: ; --tw-numeric-spacing: ; --tw-numeric-fraction: ; --tw-ring-inset: ; --tw-ring-offset-width: 0px; --tw-ring-offset-color: #fff; --tw-ring-color: rgba(69,89,164,.5); --tw-ring-offset-shadow: 0 0 transparent; --tw-ring-shadow: 0 0 transparent; --tw-shadow: 0 0 transparent; --tw-shadow-colored: 0 0 transparent; --tw-blur: ; --tw-brightness: ; --tw-contrast: ; --tw-grayscale: ; --tw-hue-rotate: ; --tw-invert: ; --tw-saturate: ; --tw-sepia: ; --tw-drop-shadow: ; --tw-backdrop-blur: ; --tw-backdrop-brightness: ; --tw-backdrop-contrast: ; --tw-backdrop-grayscale: ; --tw-backdrop-hue-rotate: ; --tw-backdrop-invert: ; --tw-backdrop-opacity: ; --tw-backdrop-saturate: ; --tw-backdrop-sepia: ; --tw-contain-size: ; --tw-contain-layout: ; --tw-contain-paint: ; --tw-contain-style: ; margin: 1.25em 0px 0px; color: rgb(13, 13, 13); font-family: Söhne, ui-sans-serif, system-ui, -apple-system, " segoe="" ui",="" roboto,="" ubuntu,="" cantarell,="" "noto="" sans",="" sans-serif,="" "helvetica="" neue",="" arial,="" "apple="" color="" emoji",="" "segoe="" ui="" symbol",="" emoji";="" font-size:="" 16px;="" white-space-collapse:="" preserve;"="">Overall, my research interest encompasses a multidisciplinary approach, integrating computational modeling, omics data analysis, and machine learning techniques to deepen our understanding of sleep and circadian rhythms, with the ultimate goal of improving human health outcomes and quality of life.

JOURNAL

1. Shiju Sisobhan, Clark Rosensweig, Bridget C Lear, Ravi Allada (2022), SleepMat: a new behavioral analysis software program for sleep and circadian rhythms, Sleep, zsac195.

2. Tomas Andreani, Clark Rosensweig, Shiju Sisobhan, Emmanuel Ogunlana, William Kath, Ravi Allada (2022) Circadian programming of the ellipsoid body sleep homeostat in Drosophila, eLife, 11:e74327.

3. Bart van Alphen, Samuel Stewart, Marta Iwanaszko, Fangke Xu, Eugenie Bang, Keyin Li, Sydney Rozenfeld, Anujaianthi Ramakrishnan, Taichi Q Itoh, Shiju S, Bridget Lear, Rosemary Braun, Ravi Allada (2021). Glial immune-related pathways mediate the effects of closed head traumatic brain injury on behavior and lethality in Drosophila PLoS Biol 20(1): e3001456.

4. Shiju S, Sriram K (2019). Multi-scale modeling of the circadian modulation of learning and memory. PLoS ONE 14(7): e0219915.

5. Shiju, S., & Sriram, K. (2019). Hilbert transform based time series analysis of the circadian gene regulatory network, IET System Biology, ISSN:1751-8849.

6. Shiju, S., & Sriram, K. (2017). Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms. PloS ONE, 12(5), e0177197.

CONFERENCE

1.         Shiju S and K Sriram. (2018, March).  A multiscale model explains the circadian phase dependent firing pattern variations in Suprachiasmatic nuclei and the occurrence of stochastic resonance, 10th International Conference on Bioinformatics and Computational Biology - BICOB-2018.

2.         Shiju, S and K, Sriram. (2016, March). Mathematical model ling of circadian oscillator that explain the role of per1 and per2 in morning and evening oscillator. Presented at ICMMDESCA-2016, Kanpur, India: Indian Institute of Technology Kanpur.

3.         Shiju S and L. Philip (2013). Memristive device with threshold for synaptic application in Neuromorphic hardwares, International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), Kottayam, 2013, pp. 229-234. doi:10.1109/iMac4s.2013.6526413.