Integral Analysis of Circadian Rhythms

Referencias bibliográficas

• Bonmati-Carrion, M.-A.; Tomas-Loba, A. Melatonin and Cancer: A Polyhedral Network Where the Source Matters. Antioxidants 2021, 10, 210 (1–42), https://doi.org/10.3390/antiox10020210.
• Gegout-Pottie, P.; Philippe, L.; Simonin, M.A.; Guingamp, C.; Gillet, P.; Netter, P.; Terlain, B. Biotelemetry: An Original Approach to Experimental Models of Inflammation. Inflamm Res 1999, 48, 417–424, https://doi.org/10.1007/s000110050481.
• Niemeyer, J.E. Telemetry for Small Animal Physiology. Lab Anim 2016, 45, 255–257, https://doi.org/10.1038/laban.1048.
• Zhang, X.; Li, H.; Gao, J. Temporal and Spatial Domain Detection Model and Method of Infrared Photoelectric Detection Target. Appl Opt 2021, 60, 7437–7445, https://doi.org/10.1364/AO.427671.
• Czech, D.A. A Versatile Integrated Circuit Activity Monitor for Small Animals. Physiol Behav 1984, 32, 871–874, https://doi.org/10.1016/0031-9384(84)90208-7.
• Zhang, C.; Li, H.; Han, R. An Open-Source Video Tracking System for Mouse Locomotor Activity Analysis. BMC Research Notes 2020, 13, 48, https://doi.org/10.1186/s13104-020-4916-6.
• Manzanares, G.; Brito-da-Silva, G.; Gandra, P.G. Voluntary Wheel Running: Patterns and Physiological Effects in Mice. Braz J Med Biol Res 2018, 52, e7830, https://doi.org/10.1590/1414-431X20187830.
• Jud, C.; Schmutz, I.; Hampp, G.; Oster, H.; Albrecht, U. A Guideline for Analyzing Circadian Wheel-Running Behavior in Rodents under Different Lighting Conditions. Biological procedures online 2005, 7, 101–116, https://doi.org/10.1251/bpo109.
• Novak, C.M.; Burghardt, P.R.; Levine, J.A. The Use of a Running Wheel to Measure Activity in Rodents: Relationship to Energy Balance, General Activity, and Reward. Neurosci Biobehav Rev 2012, 36, 1001–1014, https://doi.org/10.1016/j.neubiorev.2011.12.012.
• American Academy of Sleep Medicine International Classification of Sleep Disorders; Third.; 2014; ISBN 9781493965786.
• te Lindert, B.H.W.; Van Someren, E.J.W. Sleep Estimates Using Microelectromechanical Systems (MEMS). Sleep 2013, 36, 781–789, https://doi.org/10.5665/sleep.2648.
• Bonmati-Carrion, M.A.; Middleton, B.; Revell, V.; Skene, D.J.; Rol, M.A.; Madrid, J.A. Circadian Phase Assessment by Ambulatory Monitoring in Humans: Correlation with Dim Light Melatonin Onset. Chronobiology international 2014, 31, 37–51, https://doi.org/10.3109/07420528.2013.820740.
• Ortiz-Tudela, E.; Martinez-Nicolas, A.; Albares, J.; Segarra, F.; Campos, M.; Estivill, E.; Rol, M.A.; Madrid, J.A. Ambulatory Circadian Monitoring (ACM) Based on Thermometry, Motor Activity and Body Position (TAP): A Comparison with Polysomnography. Physiology & behavior 2014, 126, 30–38, https://doi.org/10.1016/j.physbeh.2013.12.009.
• Sadeh, A.; Sharkey, K.M.; Carskadon, M.A. Activity-Based Sleep-Wake Identification: An Empirical Test of Methodological Issues. Sleep 1994, 17, 201–207.
• Middelkoop, H.A.; van Dam, E.M.; Smilde-van den Doel, D.A.; Van Dijk, G. 45-Hour Continuous Quintuple-Site Actimetry: Relations between Trunk and Limb Movements and Effects of Circadian Sleep-Wake Rhythmicity. Psychophysiology 1997, 34, 199–203.
• Tahmasian, M.; Khazaie, H.; Sepehry, A.A.; Russo, M.B. Ambulatory Monitoring of Sleep Disorders. JPMA. The Journal of the Pakistan Medical Association 2010, 60, 480–487.
• Sarabia, J.A.; Rol, M.Á.; Mendiola, P.; Madrid, J.A. Circadian Rhythm of Wrist Temperature in Normal-Living Subjects: A Candidate of New Index of the Circadian System. Physiology & behavior 2008, 95, 570–580, https://doi.org/10.1016/j.physbeh.2008.08.005.
• Kräuchi, K. The Thermophysiological Cascade Leading to Sleep Initiation in Relation to Phase of Entrainment. Sleep medicine reviews 2007, 11, 439–451, https://doi.org/10.1016/j.smrv.2007.07.001.
• Arguelles-Prieto, R.; Bonmati-Carrion, M.-A.; Rol, M.A.; Madrid, J.A. Determining Light Intensity, Timing and Type of Visible and Circadian Light from an Ambulatory Circadian Monitoring Device. Frontiers in Physiology 2019, 10, 1–10, https://doi.org/10.3389/fphys.2019.00822.
• Markvart, J.; Hansen, Å.M.; Christoffersen, J. Comparison and Correction of the Light Sensor Output from 48 Wearable Light Exposure Devices by Using a Side-by-Side Field Calibration Method. LEUKOS - Journal of Illuminating Engineering Society of North America 2015, 11, 155–171, https://doi.org/10.1080/15502724.2015.1020948.
• Bará, S.; Bonmati-Carrion, M.A.; Madrid, J.A.; Rol, M.A.; Zamorano, J. Multispectral Estimation of Retinal Photoreceptoral Inputs. Photonics Letters of Poland 2019, 11, 60–62, https://doi.org/10.4302/plp.v11i3.920.
• Madrid-Navarro, C.J.; Escamilla-Sevilla, F.; Mínguez-Castellanos, A.; Campos, M.; Ruiz-Abellán, F.; Madrid, J.A.; Rol, M.A. Multidimensional Circadian Monitoring by Wearable Biosensors in Parkinson’s Disease. Frontiers in Neurology 2018, 9, 157, https://doi.org/10.3389/fneur.2018.00157.
• Ortiz-Tudela, E.; Martinez-Nicolas, A.; Campos, M.; Rol, M.Á.; Madrid, J.A. A New Integrated Variable Based on Thermometry, Actimetry and Body Position (TAP) to Evaluate Circadian System Status in Humans. PLoS computational biology 2010, 6, e1000996, https://doi.org/10.1371/journal.pcbi.1000996.
• Bonmatí-Carrión, M.-Á.; Casado-Ramírez, E.; Moreno-Casbas, M.T.; Campos, M.; Consortium, M.; Madrid, J.A.; Rol, M.-A. Living at the Wrong Time: Effects of Unmatching Official Time in Portugal and Western Spain. Biology 2022, 11, 1–21, https://doi.org/10.3390/biology11081130.
• Madrid-Navarro, C.J.; Puertas Cuesta, F.J.; Escamilla-Sevilla, F.; Campos, M.; Ruiz Abellán, F.; Rol, M.A.; Madrid, J.A. Validation of a Device for the Ambulatory Monitoring of Sleep Patterns: A Pilot Study on Parkinson’s Disease. Frontiers in Neurology 2019, 10, 356, https://doi.org/10.3389/fneur.2019.00356.
• Lewis, P.; Oster, H.; Korf, H.W.; Foster, R.G.; Erren, T.C. Food as a Circadian Time Cue - Evidence from Human Studies. Nature reviews. Endocrinology 2020, 16, 213–223, https://doi.org/10.1038/S41574-020-0318-Z.
• Pendergast, J.S.; Yamazaki, S. The Mysterious Food-Entrainable Oscillator: Insights from Mutant and Engineered Mouse Models. Journal of Biological Rhythms 2018, 33, 458–474.
• Challet, E. The Circadian Regulation of Food Intake. Nature reviews. Endocrinology 2019, 15, 393–405, https://doi.org/10.1038/S41574-019-0210-X.
• Rol de Lama, M.; Sánchez-Pérez, J.; Ordoñez, M. Técnicas de Estudio Del Sistema Circadiano. Cronobilogía básica y clínica 2006, 123–150.
• Dashti, H.S.; Scheer, F.A.J.L.; Saxena, R.; Garaulet, M. Timing of Food Intake: Identifying Contributing Factors to Design Effective Interventions. Advances in nutrition (Bethesda, Md.) 2019, 10, 606–620, https://doi.org/10.1093/ADVANCES/NMY131.
• Gill, S.; Panda, S. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans That Can Be Modulated for Health Benefits. Cell metabolism 2015, 22, 789–798, https://doi.org/10.1016/J.CMET.2015.09.005.
• Yatani, K.; Truong, K.N. A Wearable Acoustic Sensor for Activity Recognition. UbiComp ‘12 2012, 1–10.
• Cheng, J.; Wille, S.; Zhou, B.; When, N.; Kunze, K.; Weppner, J.; Rheinländer, C.C.; Lukowicz, P. Activity Recognition and Nutrition Monitoring in Every Day Situations with a Textile Capacitive Neckband. UbiComp 2013 Adjunct - Adjunct Publication of the 2013 ACM Conference on Ubiquitous Computing 2013, 155–158, https://doi.org/10.1145/2494091.2494143.
• Sazonov, E.; Schuckers, S.; Lopez-Meyer, P.; Makeyev, O.; Sazonova, N.; Melanson, E.L.; Neuman, M. Non-Invasive Monitoring of Chewing and Swallowing for Objective Quantification of Ingestive Behavior. Physiological measurement 2008, 29, 525–541, https://doi.org/10.1088/0967-3334/29/5/001.
• Hongu, N.; Pope, B.T.; Bilgiç, P.; Orr, B.J.; Suzuki, A.; Kim, A.S.; Merchant, N.C.; Roe, D.J. Usability of a Smartphone Food Picture App for Assisting 24-Hour Dietary Recall: A Pilot Study. Nutrition research and practice 2015, 9, 207–212, https://doi.org/10.4162/NRP.2015.9.2.207.
• Bayliss, L.; Wu, L. Should You “Picture” This? Effects of Picture-Taking Features of Food Diary Apps on Memory, Liking, and Wanting. Appetite 2022, 168, https://doi.org/10.1016/J.APPET.2021.105682.
• Thomaz, E.; Essa, I.; Abowd, G.D. A Practical Approach for Recognizing Eating Moments with Wrist-Mounted Inertial Sensing. Proceedings of the ... ACM International Conference on Ubiquitous Computing. UbiComp (Conference) 2015, 2015, 1029, https://doi.org/10.1145/2750858.2807545.
• McHill, A.W.; Hilditch, C.J.; Fischer, D.; Czeisler, C.A.; Garaulet, M.; Scheer, F.A.J.L.; Klerman, E.B. Stability of the Timing of Food Intake at Daily and Monthly Timescales in Young Adults. Scientific Reports 2020, 10, https://doi.org/10.1038/S41598-020-77851-Z.
• Panda, S. Circadian Physiology of Metabolism. Science 2016, 354, 1008–1015, https://doi.org/10.1126/science.aah4967.Circadian.
• Wittmann, M.; Dinich, J.; Merrow, M.; Roenneberg, T. Social Jetlag: Misalignment of Biological and Social Time. Chronobiology international 2006, 23, 497–509, https://doi.org/10.1080/07420520500545979.
• Zerón-Rugerio, M.F.; Hernáez, Á.; Porras-Loaiza, A.P.; Cambras, T.; Izquierdo-Pulido, M. Eating Let Lag: A Marker of the Variability in Meal Timing and Its Association with Body Mass Index. Nutrients 2019, 11, https://doi.org/10.3390/NU11122980.
• Zerón-rugerio, M.F.; Longo-silva, G.; Hernáez, Á.; Ortega-regules, A.E.; Cambras, T.; Izquierdo-pulido, M. The Elapsed Time between Dinner and the Midpoint of Sleep Is Associated with Adiposity in Young Women. Nutrients 2020, 12, https://doi.org/10.3390/NU12020410.
• St. Hilaire, M.A.; Lockley, S.W. Measuring Dim Light Melatonin Onset in Humans. In Melatonin: Methods and Protocols; Jockers, R., Cecon, E., Eds.; Methods in Molecular Biology; Springer US: New York, NY, 2022; pp. 13–20 ISBN 978-1-07-162593-4.
• Bonmati-Carrion, M.A.; Arguelles-Prieto, R.; Martinez-Madrid, M.J.; Reiter, R.; Hardeland, R.; Rol, M.A.; Madrid, J.A. Protecting the Melatonin Rhythm through Circadian Healthy Light Exposure. International journal of molecular sciences 2014, 15, 23448–23500, https://doi.org/10.3390/ijms151223448.
• Pandi-Perumal, S.R.; Smits, M.; Spence, W.; Srinivasan, V.; Cardinali, D.P.; Lowe, A.D.; Kayumov, L. Dim Light Melatonin Onset (DLMO): A Tool for the Analysis of Circadian Phase in Human Sleep and Chronobiological Disorders. Progress in neuro-psychopharmacology & biological psychiatry 2007, 31, 1–11, https://doi.org/10.1016/j.pnpbp.2006.06.020.
• Voultsios, A.; Kennaway, D.J.; Dawson, D. Salivary Melatonin as a Circadian Phase Marker: Validation and Comparison to Plasma Melatonin. J Biol Rhythms 1997, 12, 457–466, https://doi.org/10.1177/074873049701200507.
• Pullman, R.E.; Roepke, S.E.; Duffy, J.F. Laboratory Validation of an In-Home Method for Assessing Circadian Phase Using Dim Light Melatonin Onset (DLMO). Sleep medicine 2012, 13, 703–706, https://doi.org/10.1016/j.sleep.2011.11.008.
• Koike, N.; Yoo, S.H.; Huang, H.C.; Kumar, V.; Lee, C.; Kim, T.K.; Takahashi, J.S. Transcriptional Architecture and Chromatin Landscape of the Core Circadian Clock in Mammals. Science (New York, N.Y.) 2012, 338, 349, https://doi.org/10.1126/SCIENCE.1226339.
• Etchegaray, J.P.; Lee, C.; Wade, P.A.; Reppert, S.M. Rhythmic Histone Acetylation Underlies Transcription in the Mammalian Circadian Clock. Nature 2003, 421, 177–182, https://doi.org/10.1038/NATURE01314.
• Valekunja, U.K.; Edgar, R.S.; Oklejewicz, M.; van der Horst, G.T.J.; O’Neill, J.S.; Tamanini, F.; Turner, D.J.; Reddy, A.B. Histone Methyltransferase MLL3 Contributes to Genome-Scale Circadian Transcription. Proc Natl Acad Sci U S A 2013, 110, 1554–1559, https://doi.org/10.1073/pnas.1214168110.
• Le Martelot, G.; Canella, D.; Symul, L.; Migliavacca, E.; Gilardi, F.; Liechti, R.; Martin, O.; Harshman, K.; Delorenzi, M.; Desvergne, B.; et al. Genome-Wide RNA Polymerase II Profiles and RNA Accumulation Reveal Kinetics of Transcription and Associated Epigenetic Changes during Diurnal Cycles. PLoS biology 2012, 10, https://doi.org/10.1371/JOURNAL.PBIO.1001442.
• Jouffe, C.; Cretenet, G.; Symul, L.; Martin, E.; Atger, F.; Naef, F.; Gachon, F. The Circadian Clock Coordinates Ribosome Biogenesis. PLoS biology 2013, 11, https://doi.org/10.1371/JOURNAL.PBIO.1001455.
• Kojima, S.; Sher-Chen, E.L.; Green, C.B. Circadian Control of MRNA Polyadenylation Dynamics Regulates Rhythmic Protein Expression. Genes & development 2012, 26, 2724–2736, https://doi.org/10.1101/GAD.208306.112.
• Morf, J.; Rey, G.; Schneider, K.; Stratmann, M.; Fujita, J.; Naef, F.; Schibler, U. Cold-Inducible RNA-Binding Protein Modulates Circadian Gene Expression Posttranscriptionally. Science (New York, N.Y.) 2012, 338, 379–383, https://doi.org/10.1126/SCIENCE.1217726.
• Reddy, A.B.; O’Neill, J.S. Healthy Clocks, Healthy Body, Healthy Mind. Trends in Cell Biology 2010, 20, 36–44, https://doi.org/10.1016/j.tcb.2009.10.005.
• Archer, S.N.; Laing, E.E.; Möller-Levet, C.S.; van der Veen, D.R.; Bucca, G.; Lazar, A.S.; Santhi, N.; Slak, A.; Kabiljo, R.; von Schantz, M.; et al. Mistimed Sleep Disrupts Circadian Regulation of the Human Transcriptome. Proceedings of the National Academy of Sciences 2014, https://doi.org/10.1073/pnas.1316335111.
• Möller-Levet, C.S.; Archer, S.N.; Bucca, G.; Laing, E.E.; Slak, A.; Kabiljo, R.; Lo, J.C.Y.Y.; Santhi, N.; von Schantz, M.; Smith, C.P.; et al. Effects of Insufficient Sleep on Circadian Rhythmicity and Expression Amplitude of the Human Blood Transcriptome. Proceedings of the National Academy of Sciences of the United States of America 2013, 110, E1132-41, https://doi.org/10.1073/pnas.1217154110.
• Minors, D.S.; Waterhouse, J.M. Mathematical and Statistical Analysis of Circadian Rhythms. Psychoneuroendocrinology 1988, 13, 443–464, https://doi.org/10.1016/0306-4530(88) 90030-3.
• Díez-Noguera, A. Representación Gráfica y Análisis de Datos En Cronobiología. In Cronobilogía básica y clínica; 2007; pp. 83–121.
• Levine, J.D.; Funes, P.; Dowse, H.B.; Hall, J.C. Signal Analysis of Behavioral and Molecular Cycles. BMC Neuroscience 2002, 3, 1, https://doi.org/10.1186/1471-2202-3-1.
• Reinberg, A.; Smolensky, M.H. Investigative Methodology for Chronobiology. In Proceedings of the Biological Rhythms and Medicine; Reinberg, A., Smolensky, M.H., Eds.; Springer: New York, NY, 1983; pp. 23–46.
• Martínez Nicolás, A.B. Crosstalk between Synchronizers and the Human Circadian System., Universidad de Murcia, 2014.
• Rueda, C.; Larriba, Y.; Peddada, S.D. Frequency Modulated Möbius Model Accurately Predicts Rhythmic Signals in Biological and Physical Sciences. Sci Rep 2019, 9, 18701, https://doi.org/10.1038/s41598-019-54569-1.
• Marín-Garciá, A.; Fossion, R.; Müller, M.F.; Ríos-Herrera, W.; Rivera, A.L. A Non-Parametric Model: Free Analysis of Actigraphic Recordings of Acute Insomnia Patients. Royal Society Open Science 2022, 9, https://doi.org/10.1098/rsos.210463.
• Rodriguez-Morilla, B.; Martínez-MAdrid, M.J.; Campos Martínez, M.; Rol de Lama, M.A.; Madrid Pérez, J.A. Monitorización Circadiana Ambulatoria (MCA).; Colegio Oficial de Biólogos de la Región de Murcia, 2021; ISBN 978-84-09-33766-8.
• Rodriguez-Morilla, B.; Estivill, E.; Estivill-Domènech, C.; Albares, J.; Segarra, F.; Correa, A.; Campos, M.; Rol, M.A.; Madrid, J.A. Application of Machine Learning Methods to Ambulatory Circadian Monitoring (ACM) for Discriminating Sleep and Circadian Disorders. Frontiers in Neuroscience 2019, 13, 1–12, https://doi.org/10.3389/fnins.2019.01318.
• Witting, W.; Kwa, I.H.; Eikelenboom, P.; Mirmiran, M.; Swaab, D.F. Alterations in the Circadian Rest ­ Activity Rhythm in Aging and Alzheimer’s Disease. Biological Psychiatry 1990, 27, 563–572, https://doi.org/10.1016/0006.
• Van Someren, E.; Swaab, D.F.; Colenda, C.C.; Cohen, W.; McCall, W.V.; Rosenquist, P.B. Bright Light Therapy: Improved Sensitivity to Its Effects on Rest-Activity Rhythms in Alzheimer Patients by Application of Nonparametric Methods. Chronobiology international 1999, 16, 505–518.
• Van Someren, E.; Swaab, D.F.; Colenda, C.C.; Cohen, W.; McCall, W.V.; Rosenquist, P.B. Bright Light Therapy: Improved Sensitivity to Its Effects on Rest-Activity Rhythms in Alzheimer Patients by Application of Nonparametric Methods. Chronobiology international 1999, 16, 505–518.
• Sokolove, P.G.; Bushell, W.N. The Chi Square Periodogram: Its Utility for Analysis of Circadian Rhythms. Journal of theoretical biology 1978, 72, 131–160.
• Van Someren, E.J.W.; Hagebeuk, E.E.O.; Lijzenga, C.; Scheltens, P.; De Rooij, S.E.J.A.; Jonker, C.; Pot, A.M.; Mirmiran, M.; Swaab, D.F. Circadian Rest-Activity Rhythm Disturbances in Alzheimer’s Disease. Biological Psychiatry 1996, 40, 259–270, https://doi.org/10.1016/0006-3223(95)00370-3.
• Scherder, E.J.A.; Van Someren, E.J.W.; Swaab, D.F. Transcutaneous Electrical Nerve Stimulation (TENS) Improves the Rest - Activity Rhythm in Midstage Alzheimer’s Disease. Behavioural Brain Research 1999, 101, 105–107, https://doi.org/10.1016/S0166-4328(98)00150-8.
• Oosterman, J.M.; Van Someren, E.J.W.; Vogels, R.L.C.; Van Harten, B.; Scherder, E.J.A. Fragmentation of the Rest-Activity Rhythm Correlates with Age-Related Cognitive Deficits. Journal of Sleep Research 2009, 18, 129–135, https://doi.org/10.1111/j.1365-2869.2008.00704.x.
• Zuurbier, L.A.; Luik, A.I.; Hofman, A.; Franco, O.H.; Van Someren, E.J.; Tiemeier, H. Fragmentation and Stability of Circadian Activity Rhythms Predict Mortality - The Rotterdam Study. American Journal of Epidemiology 2015, 181, 54–63, https://doi.org/10.1093/aje/kwu245.
• Ortiz-Tudela, E.; Innominato, P.F.; Rol, M.A.; Lévi, F.; Madrid, J.A. Relevance of Internal Time and Circadian Robustness for Cancer Patients. BMC Cancer 2016, 16, https://doi.org/10.1186/s12885-016-2319-9.
• Bonmati-Carrion, M.A.; Hild, K.; Isherwood, C.; Sweeney, S.J.; Revell, V.L.; Skene, D.J.; Rol, M.A.; Madrid, J.A. Relationship between Human Pupillary Light Reflex and Circadian System Status. PloS one 2016, 11, e0162476, https://doi.org/10.1371/journal.pone.0162476.
• Martinez-Nicolas, A.; Guaita, M.; Santamaría, J.; Montserrat, J.M.; Rol, M.Á.; Madrid, J.A. Circadian Impairment of Distal Skin Temperature Rhythm in Patients with Sleep-Disordered Breathing: The Effect of CPAP. Sleep 2017, 40, https://doi.org/10.1093/sleep/zsx067.
• Martinez-Nicolas, A.; Madrid, J.A.; García, F.J.; Campos, M.; Moreno-Casbas, M.T.; Almaida-Pagán, P.F.; Lucas-Sánchez, A.; Rol, M.A. Circadian Monitoring as an Aging Predictor. Scientific Reports 2018, 8, 15027, https://doi.org/10.1038/s41598-018-33195-3.
• Martinez-Nicolas, A.; Martinez-Madrid, M.J.; Almaida-Pagan, P.F.; Bonmati-Carrion, M.-A.; Madrid, J.A.; Rol, M.A. Assessing Chronotypes by Ambulatory Circadian Monitoring. Frontiers in Physiology 2019, 10, 1396, https://doi.org/10.3389/FPHYS.2019.01396.
• Zornoza-Moreno, M.; Fuentes-Hernández, S.; Sánchez-Solis, M.; Rol, M.Á.; Larqué, E.; Madrid, J.A. Assessment of Circadian Rhythms of Both Skin Temperature And motor Activity in Infants during the First 6 Months of Life. Chronobiol Int 2011, 28, 330–337, https://doi.org/10.3109/07420528.2011.565895.
• Fisher, N.I. Statistical Analysis of Circular Data; Cambridge University Press: Cambridge, 1993; ISBN 978-0-521-56890-6.
• Landler, L.; Ruxton, G.D.; Malkemper, E.P. Circular Data in Biology: Advice for Effectively Implementing Statistical Procedures. Behav Ecol Sociobiol 2018, 72, 128, https://doi.org/10.1007/s00265-018-2538-y.
• Klerman, E.B.; Wang, W.; Phillips, A.J.K.; Bianchi, M.T. Statistics for Sleep and Biological Rhythms Research: Longitudinal Analysis of Biological Rhythms Data. J Biol Rhythms 2017, 32, 18–25, https://doi.org/10.1177/0748730416670051.
• Díez-Noguera, A. Methods for Serial Analysis of Long Time Series in the Study of Biological Rhythms. Journal of circadian rhythms 2013, 11, 7, https://doi.org/10.1186/1740-3391-11-7.
• Plautz, J.D.; Straume, M.; Stanewsky, R.; Jamison, C.F.; Brandes, C.; Dowse, H.B.; Hall, J.C.; Kay, S.A. Quantitative Analysis of Drosophila Period Gene Transcription in Living Animals. Journal of Biological Rhythms 1997, 12, 204–217, https://doi.org/10.1177/074873049701200302.
• RuedaSabater, C.; Rodríguez-Collado, A.; Larriba, Y. A Novel Wave Decomposition for Oscillatory Signals. IEEE Transactions on Signal Processing 2021, 69, 960–972, https://doi.org/10.1109/TSP.2021.3051428.
• Czeisler, C.A. The Effect of Light on the Human Circadian Pacemaker. Ciba Foundation symposium 1995, 183, https://doi.org/10.1002/9780470514597.CH14.
• Jewett, M.E.; Forger, D.B.; Kronauer, R.E. Revised Limit Cycle Oscillator Model of Human Circadian Pacemaker. Journal of biological rhythms 1999, 14, 493–500, https://doi.org/10.1177/074873049901400608.
• Jewett, M.E.; Kronauer, R.E. Refinement of a Limit Cycle Oscillator Model of the Effects of Light on the Human Circadian Pacemaker. Journal of Theoretical Biology 1998, 192, 455–465, https://doi.org/10.1006/jtbi.1998.0667.
• Kronauer, R.E.; Czeisler, C.A.; Pilato, S.F.; Moore-Ede, M.C.; Weitzman, E.D. Mathematical Model of the Human Circadian System with Two Interacting Oscillators. The American journal of physiology 1982, 242, https://doi.org/10.1152/AJPREGU.1982.242.1.R3.
• Daan, S.; Beersma, D.G.M.; Borbely, A.A. Timing of Human Sleep: Recovery Process Gated by a Circadian Pacemaker. The American journal of physiology 1984, 246, https://doi.org/10.1152/AJPREGU.1984.246.2.R161.
• Borbély, A.A. A Two Process Model of Sleep Regulation. Hum Neurobiol 1982, 1, 195–204.
• Khalsa, S.B.S.; Jewett, M.E.; Cajochen, C.; Czeisler, C.A. A Phase Response Curve to Single Bright Light Pulses in Human Subjects. The Journal of physiology 2003, 549, 945–952, https://doi.org/10.1113/jphysiol.2003.040477.
• Kronauer, R.E. A Quantitative Model for the Effects of Light on the Amplitude and Phase of the Deep Circadian Pacemaker, Based on Human Data. In Proceedings of the Tenth European Congress on Sleep Research; Pontenagel Press: Düsseldorf, 1990; p. 306.
• Forger, D.B.; Jewett, M.E.; Kronauer, R.E. A Simpler Model of the Human Circadian Pacemaker. Journal of biological rhythms 1999, 14, 533–538, https://doi.org/10.1177/074873099129000867.
• St. Hilaire, M.A.; Klerman, E.B.; Khalsa, S.B.S.; Wright, K.P.; Czeisler, C.A.; Kronauer, R.E. Addition of a Non-Photic Component to a Light-Based Mathematical Model of the Human Circadian Pacemaker. Journal of theoretical biology 2007, 247, 583–599, https://doi.org/10.1016/J.JTBI.2007.04.001.
• van der Pol, Balth. LXXXVIII. On “Relaxation-Oscillations.” The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 1926, 2, 978–992, https://doi.org/10.1080/14786442608564127.
• Aschoff, J. Xogenous and Endogenous Components in Circadian Rhythms. Cold Spring Harbor symposia on quantitative biology 1960, 25, 11–28, https://doi.org/10.1101/SQB.1960.025.01.004.
• Borbély, A.A.; Baumann, F.; Brandeis, D.; Strauch, I.; Lehmann, D. Sleep Deprivation: Effect on Sleep Stages and EEG Power Density in Man. Electroencephalography and clinical neurophysiology 1981, 51, 483–493, https://doi.org/10.1016/0013-4694(81)90225-X.
• Asgari-Targhi, A.; Klerman, E.B. Mathematical Modeling of Circadian Rhythms. Wiley interdisciplinary reviews. Systems biology and medicine 2019, 11, https://doi.org/10.1002/WSBM.1439.
• Booth, V.; Diniz Behn, C.G. Physiologically-Based Modeling of Sleep-Wake Regulatory Networks. Mathematical biosciences 2014, 250, 54–68, https://doi.org/10.1016/J.MBS.2014.01.012.
• Hannay, K.M.; Booth, V.; Forger, D.B. Macroscopic Models for Human Circadian Rhythms. Journal of biological rhythms 2019, 34, 658–671, https://doi.org/10.1177/0748730419878298.
• Phillips, A.J.K.; Robinson, P.A. A Quantitative Model of Sleep-Wake Dynamics Based on the Physiology of the Brainstem Ascending Arousal System. Journal of biological rhythms 2007, 22, 167–179, https://doi.org/10.1177/0748730406297512.
• Papatsimpa, C.; Schlangen, L.J.M.; Smolders, K.C.H.J.; Linnartz, J.P.M.G.; de Kort, Y.A.W. The Interindividual Variability of Sleep Timing and Circadian Phase in Humans Is Influenced by Daytime and Evening Light Conditions. Scientific Reports 2021, 11, 1–14, https://doi.org/10.1038/s41598-021-92863-z.